The author(s) shown below used Federal funds provided by the U.S. 

Department of Justice and prepared the following final report: 

Document Title: The Transfer of Responsibility for Child 

Protective Investigations to Law Enforcement in 

Florida: A Supplemental Study Final Report 

Author(s): Susan Kinnevy, Ph.D.; Vera Huang, M.S.; 

Melissa Dichter, M.S.W.; Richard Gelles, Ph.D. 

Document No.: 210489 

Date Received: July 2005 

Award Number: 2000-IJ-CX-0002 

This report has not been published by the U.S. Department of Justice. 

To provide better customer service, NCJRS has made this Federallyfunded grant final report available electronically in addition to

traditional paper copies.

 

Opinions or points of view expressed are those 

of the author(s) and do not necessarily reflect 

the official position or policies of the U.S. 

Department of Justice.
THE TRANSFER OF RESPONSIBILITY 

FOR CHILD PROTECTIVE INVESTIGATIONS 

TO LAW ENFORCEMENT IN FLORIDA: 

A SUPPLEMENTAL STUDY 

FINAL REPORT 

Prepared by: 

Susan Kinnevy, PhD 

Vera Huang, MS 

Melissa Dichter, MSW

Richard Gelles, PhD 

February 2005 

CENTER FOR RESEARCH ON YOUTH 

AND SOCIAL POLICY

SCHOOL OF SOCIAL WORK 

UNIVERSITY OF PENNSYLVANIA 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
TABLE OF CONTENTS 

EXECUTIVE SUMMARY............................................................. i 

I. Background and Significance 1 

II. Overview of Original Study............................................................ 5 

III. Summary of Findings from Original Study.......................................... 10 

IV. Current Supplemental Study................................................................. 16 

V. Criminal Court and the Link the Child Welfare..................................... 19 

A. Overview............................................................................ 19 

B. Sample Description................................................................ 19 

C. Results: Tracking Back from Criminal Disposition to Original 

Report................................................................................ 22 

D. Summary of Findings on the Link between Child Welfare and Criminal 

Sanctions............................................................................. 32 

VI. Secondary Analysis of Child Welfare Data (FAHIS 1996-2002)........................ 35 

A. Analytic Plan....................................................................... 35 

B. Administrative Data............................................................... 39 

C. Sample Description............................................................... 39 

D. Results: Analyses of County Pairs.................................................... 41 

I. Reports Filed for Investigation.............................................. 41 

II. Substantiation.................................................................. 42 

III. Severity......................................................................... 45 

IV. Duration........................................................................ 48 

V. Recurrence and Recidivism................................................... 53 

E. Summary of County Pair Analyses................................................ 55 

VII. Event History Analyses of Child Welfare Data (FAHIS 1996-2002).............. 57 

A. Hazard Function Analysis.................................................................... 57 

B. Survivor Analysis Using Proportional Hazard Functions (Cox 

Regression)............................................................................

76 

C. Median Lifetime Analyses.......................................................... 87 

D. Summary of Event History Analyses............................................. 89 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
VIII. Performance of Sheriff Offices in Child Maltreatment 

Investigations,.............................................................................. 91 

A. Replication of County Pair Analyses for Sheriff vs Non-Sheriff.............. 91 

B. Florida’s Statewide Performance Indicators...................................... 95 

C. Summary of Findings on Performance of Sheriff Offices...................... 99 

IX. Summary Comparison Across Measures................................................ 101 

A. County Comparison Across Analytic Measures................................. 101 

B. Sheriff vs Non-Sheriff Comparison Across All Measures...................... 102 

C. Comparison of Findings from Original and Supplemental Studies............ 103 

X. Conclusion.................................................................................. 103 

References.................................................................................. 105 

Appendices 

A. Population Census (2000) Data for 8 Counties and County Pair Data on 

Caretakers, Victims and Children................................................ 107 

B. Breakdown of Odds Ratio for Substantiation by County and County 

Pairs.................................................................................. 110 

C. Hazard Function Graphs and Statistical Support: 24 month 

Duration.............................................................................. 127 

D. Survival Estimates for Recurrence and Recidivism by County 

Pair.................................................................................. 134 

E. Estimated Survival Probabilities for Recurrence and Recidivism: Median 

Lifetime Duration in Days............................................ 141 

F. Statistical Support for Sheriff vs Non-Sheriff: Odds Ratio Estimates, 

Survival Estimates, and Survival Probabilities................................ 143 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
LIST OF TABLES, FIGURES, CHARTS AND GRAPHS 

Figure 1. Organization of Sheriff’s Offices.................................... 6 

Figure 2. Traditional Investigative Process in DCF Counties............... 8 

Figure 3 Investigative Process in Sheriff’s Counties......................... 9 

Table 1. Demographics of Experimental and Comparison Counties...... 10 

Table 2. Family Dataset Sizes Sheriff and Non-Sheriff Counties.......... 11 

Table 3. SAO Original Sample.................................................. 20 

Table 4. BSO Search Sample................................................... 20 

Table 5. Outcomes for Disposed Cases in Search Sample.................. 21 

Figure 4. Data Tracking Protocol................................................ 22 

Table 6. Comparison of Reports Found and Not Found..................... 23 

Table 7. Comparison of Disposed and Not-Disposed Reports in Found 

Reports.................................................................. 24 

Figure 5. Comparison of Mean Number of Allegations and Findings...... 24 

Figure 6. Types of Allegations by Disposition Status........................ 25 

Figure 7. Types of Findings by Disposition Status........................... 25 

Table 8. Reports by Substantiation Status..................................... 26 

Figure 8. Relationship between Perpetrator and Child....................... 26 

Figure 9. Type of Criminal Charge by Disposition Status.................. 27 

Figure 10. Degree of Criminal Charge by Disposition Status............... 27 

Figure 11. Type and Degree of Charge by Disposition Status............... 28 

Table 9. Distribution of Relevant Variables in Disposed Cases............ 28 

Figure 12. Distribution of Maltreatment Allegations by Type................ 29 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 13. Distribution of Criminal Charges by Type and Degree........... 29 

Figure 14. Relationship between Criminal Charges and Criminal 

Sanctions................................................................ 30 

Table 10. Report Distribution from Allegation through Sanctions......... 30 

Figure 15. Relationship of Perpetrator to Child................................ 31 

Figure 16. Results of Implementing the Tracking Protocol.................. 32 

Figure 17. Pilot: Feedback Loop between BSO and SAO..................... 34 

Table 11. Description of County Pairs and Time Periods..................... 35 

Table 12. Operational Definitions of Outcome Measures.................... 36 

Table 13. Analytic Plan........................................................... 37 

Table 14. Sample Description: Number of Reports.......................... 40 

Table 15. Sample Description: Number of Families.......................... 41 

Table 16. Impact of Experimental Stage on Number of Reports............ 42 

Table 17. Pre-Post Difference in Percent of Substantiated Reports......... 43 

Table 18. Odds (percentage) of Substantiation by County Pair.............. 44 

Table 19. Effect Size Impact of Transfer on Substantiation by County 

Pair....................................................................... 44 

Table 20. Pre-Post Difference in Percent of Reports Substantiated with 

High Index Maltreatment Severity................................... 46 

Table 21. Effect Size Impact of Transfer on Maltreatment Severity........ 46 

Table 22. Pre-Post Difference in Percent of Reports Substantiated with 

High Index Disposition Severity..................................... 47 

Table 23. Effect Size Impact of Transfer on Disposition Severity.......... 48 

Table 24. OLS Estimates for Time to Investigative Finding and Time to 

Case Closing/Services Open.......................................... 49 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 25 Pre-Post Change in Time to Investigative Finding (mean # 

days)..................................................................... 50 

Table 26. Effect Size Impact on Time to Investigative Finding by County 

Pair....................................................................... 51 

Table 27. Pre-Post Change in Time to Case Closing/Services Open 

(mean # days)........................................................... 52 

Table 28. Effect Size Impact on Time to Case Closing/Services Open by 

County Pair.............................................................. 52 

Table 29. Pre-Post Percentage Change in Families with 

Recurrence.............................................................. 54 

Table 30. Pre-Post Percentage Change in Families with Recidivism....... 55 

Figure 16. Comparison between Percent Changes in Recurrence and 

Recidivism.............................................................. 

. 

55 

Table 31. Number of Families for Recurrence and Recidivism Hazard 

Function Model: 18 month Duration............................... 

. 

58 

Table 32. Hazard Function Statistics for County Pair 1: ManateeLee........................................................................ 60 

Graphs Manatee-Lee Recurrence and Recidivism Hazard................. 61-62 

Table 33. Hazard Function Statistics for County Pair 2: ManateeSarasota.................................................................. 63 

Graphs Manatee-Sarasota Recurrence and Recidivism Hazard........... 64-65 

Table 34. Hazard Function Statistics for County Pair 2: PinellasHillsborough............................................................ 66 

Graphs Pinellas-Hillsborough Recurrence and Recidvism Hazard...... 67-68 

Table 35. Hazard Function Statistics for County Pair 2: PascoLee........................................................................ 69 

Graphs Pasco-Lee Recurrence and Recidivism Hazard.................... 70-71 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 36. Hazard Function Statistics for County Pair 2: Broward- Palm 

Beach..................................................................... 72 

Graphs Broward-Palm Beach Recurrence and Recidivism Hazard...... 73-74 

Table 37. Significant Predictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 1: Manatee-Lee... 77 

Graphs Manatee-Lee Recurrence and Recidivism Survival............... 78 

Table 38. Significant Predictors Model for Recurrence and Recidivism 

for County Pair 2: Manatee-Sarasota............................... 79 

Graphs Manatee-Sarasota Recurrence and Recidivism Survival......... 80 

Table 39. Significant Predictors for Recurrence and Recidivism for 

County Pair 3: Pinellas-Hillsborough...................................... 81 

Graphs Pinellas-Hillsborough Recurrence and Recidivism Survival..... 82 

Table 40. Significant Predictors for Recurrence and Recidivism for 

County Pair 4: Pasco-Lee 2.......................................... 83 

Graphs Pasco-Lee2 Recurrence and Recidivism Survival................. 84 

Table 41. Significant Predictors for Recurrence and Recidivism for 

County Pair 5: Broward – Palm Beach............................. 85 

Graphs Broward-Palm Beach Recurrence and Recidivism Survival...... 86 

Table 42. Median Lifetime Estimates of Survival Probability in Months 

(p=.50)................................................................... 87 

Figure 18. Estimated Time to Recurrence in Months........................... 88 

Figure 19. Estimated Time to Recidivism in Months........................... 88 

Figure 20. Pre-Post Increase in Survival Time in Months..................... 88 

Figure 21. Pre-Post Difference in Time Between Recurrence and 

Recidivism............................................................... 89 

Table 43. Change in Odds Ratio for Substantiation, Sheriff vs NonSheriff Counties......................................................... 91 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 22. Change in Percentage of Reports: Substantiation, Recurrence, 

and Recidivism, Sheriff vs Non-Sheriff Counties.................. 92 

Figure 23. Effect Size Comparison: Maltreatment and Disposition 

Severity, Sheriff vs Non-Sheriff Counties.......................... 92 

Figure 24. Effect Size comparison: Time to Finding and Time to Case 

Closing/Open Services, Sheriff vs Non-Sheriff Counties......... 93 

Figure 25. Mean # of Days to Finding and Case Closing, Sheriff vs NonSheriff Counties......................................................... 93 

Graphs. Hazard Functions and Survival Curves, Sheriff vs Non-Sheriff 

Counties................................................................. 94 

Figure 27. Median Lifetime Estimates of Survival Probability in Months 

(p=.50) for Recurrence and Recidivism Sheriff vs Non-Sheriff 

Counties............................................................... 95 

Figure 28. Overall Ranking for Florida’s Child Welfare Investigative 

Agencies................................................................. 96 

Figure 29. Ranking for Sheriff Counties Only................................. 97 

Figure 30. Comparison of Rankings, Sheriff vs Non-Sheriff Counties...... 98 

Figure 31. Average Rank for Investigations Commenced on Time.......... 98 

Figure 32. Average Rank For Investigations Closed in 60 Days............. 99 

Table 44. Ranking of Experimental and Comparison Counties on 

Statewide Indicators................................................... 100 

Table 45. County Pair Comparisons Across Analytic Measures............ 101 

Table 46. Sheriff vs Non-Sheriff Comparison Across Measures............ 102 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
EXECUTIVE SUMMARY 

In May 1998, the Florida legislature mandated the transfer of responsibility for 

child protective investigations in Manatee, Pinellas, and Pasco Counties from the 

Department of Children and Families (DCF) to the Sheriff’s Offices (SO) in those 

counties. Subsequently, Broward County Sheriff’s Office voluntarily agreed to accept 

this responsibility as well. The Sheriff’s Offices agreed on a common investigative 

protocol that teamed civilian Child Protective Investigators (CPIs) with Sheriff’s 

Deputies or local law enforcement officers to investigate all reports of child 

maltreatment. 

 

The National Institute of Justice, the Office of Juvenile Justice Delinquency and 

Prevention, and the Florida Department of Children and Families funded the Center for 

the Study of Youth Policy at the University of Pennsylvania School of Social Work (now 

known as the Center for Research on Youth and Social Policy) to evaluate the impact of 

this change in both experimental and comparison counties. Comparison counties were 

matched on selected demographic and caseload similarity. Lee was used as the 

comparison county for both Manatee and Pasco; Hillsborough was used as the 

comparison county for Pinellas; and Palm Beach was used as a comparison county for 

Broward. 

The evaluation was completed in 2003. Findings from the study were 

inconclusive with regard to the impact of the law enforcement experiment. There were 

intermittent positive changes in measures of child safety; these changes, however, 

affected comparison as well as experimental counties. The relationship between 

investigations and service delivery was also explored, but percentages of children served 

relative to services mandated demonstrated no discernable connection to the law 

enforcement experiment. The available data yielded no findings on the relationship 

between child maltreatment and criminal sanctions for perpetrators, although aggregate 

data showed no major changes pre-post in arrest, incarceration, or probation patterns. 

Interview and survey responses indicated that Child Protective Investigators were 

more satisfied with their jobs in the experimental counties. Child Protection Team

members express satisfaction with improvements over time in working with the Sheriff’s 

Offices, but also indicate a comparative preference for working with DCF. Judges, 

attorneys, and law enforcement officers are generally satisfied with the investigations

being conducted by the Sheriff’s Offices, but also agreed that it was too soon to tell if the 

experiment has had any lasting impact. Case file documentation improved in the 

experimental counties as well as the comparison counties; the lack of useable data on 

arrest, prosecution and family court proceedings made it impossible to assess the impact 

of documentation on disposition. 

Overall, findings indicated that the law enforcement intervention has not proved 

as successful as its proponents had hoped. Furthermore, the answer to the question 

regarding the experiment’s impact on criminal sanctions for perpetrators remained 

Center for the Study of Youth Policy University of Pennsylvania

i

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
unanswered. The current study is designed to supplement findings from the original 

study and is structured to accommodate changes in the Florida data system. The purpose 

of the current study is three-fold: 1) To create a larger and more comprehensive analytic 

dataset in order to conduct a series of more rigorous analyses on the data to answer the 

original research questions more definitively; 2) To create and implement a protocol for 

tracking outcomes for perpetrators through an exploration of the criminal court data and 

an attempted link between court and child welfare data; to analyze results; and to explore 

possibilities for institutionalizing data integration between the two systems; and 3) To 

examine the operation of the new Florida child welfare data system, Home Safe Net 

(HSN). 

The design of the current study is primarily secondary data analysis of existing 

and supplemental administrative data with an emphasis on data integration within and 

between data systems. The quantitative analyses focus on outcome measures related to 

the law enforcement experiments, e.g. substantiation, severity, recidivism. The data 

integration protocol is exploratory, focusing on the theoretical possibilities for integration 

based on the implementation of a pilot protocol. For purposes of clarity, the following 

report is divided into three sections: 1) Criminal Court Data and the Link to Child 

Welfare; 2) Secondary Data Analyses of Child Welfare Data, 1996 - 2002; and 3) 

Performance of Sheriff’s Offices in Child Maltreatment Investigations. Findings are 

summarized below. 

Criminal Court Data and the Link to Child Welfare

Findings from Section 1 on the link between criminal court and child welfare data 

are limited because the court would not release names necessary for matching on cases

that were either pending or dismissed; therefore, it is not possible to say if the match 

between the two datasets produced a sample that is representative of the whole. 

However, analysis of relevant variables – demographics, number and type of allegations, 

type of disposition, and time between offense, arrests, and disposition – found no 

significant differences between disposed cases in the whole sample and those matched 

with child welfare data. Likewise, no significant differences were found between reports 

that were matched and those that were not. It is at least possible, then, that the analytic 

sample is similar enough to the sample as a whole to make the findings contributory to 

the literature on criminalization of child abuse, although this section of the study must be 

viewed as exploratory rather than explanatory. 

The court provided 235 reports with appropriate identifiers and the matching 

protocol yielded 128 reports for analysis. Within this sample, type of allegation and 

relationship to the child did not prove significantly different for disposed cases. The type 

and degree of charge were not related to disposition when analyzed separately, but were 

significantly related when collapsed and combined into a single variable. Disposed cases 

consisted primarily of substantiated allegations of physical abuse resulting in 3rd degree 

felony charges. Almost one-third of disposed cases resulted in either probation or a jail 

sentence, although only the relationship between probation and the degree of the charge 

proved significant. The most commonly reported relationship in the disposed cases was 

Center for the Study of Youth Policy University of Pennsylvania

ii

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
between mother and child. None of the relationships, however, were significantly 

associated with specific probation or sentence time. Overall, only 35.9% of reports found 

through the tracking protocol received criminal sanctions. 

Secondary Data Analyses of Child Welfare Data (1996-2002): County Pairs

Overall, the analyses of county pairs suggest that the impact of law enforcement 

experiment is negligible, with significant effects often applicable to both experimental 

and comparison counties, suggesting that the transfer alone did not account for the 

impact. The odds percentage of a report being substantiated increased in four of the five 

county pairs in the post experimental stage, but the impact was not large enough to be 

policy relevant. With regard to changes in maltreatment and disposition severity, the 

experiment seems to have little impact on either. With regard to duration of investigation 

and length of time to services, OLS estimates establish that neither variable was 

responsible for more than a small percentage of variance in their models. The findings on 

recurrence and recidivism are inconclusive, although recurring reports were more 

common than substantiated recurring reports. The findings were also difficult to interpret 

because an administrative change in the Florida Abuse Hotline directly influenced an 

increase in the number of reports received, making it difficult to attribute changes in 

reports to the law enforcement experiment. 

Event History Analyses of Child Welfare Data (1996-2002)

The hazard function models illustrate an increased rate for all counties, but also 

illustrate an influence in the Sheriff counties on achieving a steady rate. Survival curves 

for recurrence are similar for all county pairs, with the post stage showing a more 

constant rate than the pre stage. The county pairs also share some significant predictors: 

maltreatment and disposition severity; family mobility; victim age; and mixed sex of 

caretaker. Survival curves for recidivism are similar to those for recurrence, although 

maltreatment severity’s impact is not shared. Overall, it seems that all county pairs are 

experiencing steady survival rates after the transfer of responsibility to the Sheriff 

Offices, making it unlikely that there is an association between the two. All counties 

increased their median lifetime survival probabilities, thereby eliminating the possibility 

of an impact from the experiment. 

Performance of Sheriff’s Offices in Child Maltreatment Investigations

With regard to report substantiation, the Sheriff counties are performing better 

than the non-Sheriff counties. The investigative transfer seems to have had no significant 

impact on maltreatment or disposition severity and a negative impact on length of 

investigation and length of time until services are delivered. The Sheriff counties are also 

performing better in decreasing recurrence, although not as well as the non-Sheriff 

counties in decreasing recidivism. Event history analyses illustrate that the hazard for 

recidivism decreases gradually in the pre stage and increases slightly in the post stage for 

both Sheriff and non-Sheriff counties, making it unlikely that either hazard or survival are 

impacted by the transfer of investigative responsibility. Using Florida’s statewide 

Center for the Study of Youth Policy University of Pennsylvania

iii

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
performance indicators as a measure of success, the Sheriff counties consistently 

outperform the non-Sheriff counties on all 11 measures. Of the Sheriff counties, 

Broward outperforms all counties with the exception of Seminole, which is not part of 

this study. 

Comparison Across Measures

When county pairs were compared across analytic measures, all counties shared a 

decrease in the percent of reports with high index level maltreatment severity; an increase 

survival rates for recurrence and recidivism; and increases in time to recurrence and 

recidivism. Although these measures are among the most desirable indicators of 

successful improvement in child safety, as all counties are improving on the measures 

simultaneously, they are not indicators of the success of the investigative transfer. When 

the Sheriff counties are compared with the non-Sheriff counties aggregated, the Sheriff 

counties outperform only on odds of substantiation, decrease in disposition severity, and 

11 statewide indicators of performance. 

Comparison of Findings from Original and Supplemental Study

The findings from this supplemental study support the original findings that the 

investigative transfer had little impact on recurrence and recidivism, although there 

seemed to be more convergence among all counties than had been previously revealed, 

i.e. all counties improved in discrete areas such as increased survival times. With regard 

to the original unanswered question regarding outcomes for perpetrators, this study was 

able to establish to some extent the percentage of perpetrators likely to experience 

criminal sanctions (35.9%) in Broward County, at least over the last year. 

Conclusions

For now, it is fair to say that the secondary data analyses presented in this report 

indicate that the transfer of investigative responsibility to law enforcement has not had 

the desired or expected impact. It is important to remember, however, that the 

experiment with law enforcement is still new, although the difficulties associated with the 

new endeavor seem to have been overcome. Viewing the investigative transfer from the 

perspective of the state-identified performance indicators, it is clear the Sheriff’s Offices 

are doing a uniformly good job in investigating child maltreatment. 

Dissemination of Findings

Plans are being finalized for publishing the findings from the original and 

supplemental studies in a Special Issue of Children and Youth Services Review. Because 

the child welfare situation in Florida is unique, primarily due to its link with law 

enforcement, the researchers feel that the findings will be better understood is they are 

presented as a whole rather than disseminated over many months or years in various 

journals. The findings have been presented, and will continue to be presented, at 

appropriate regional and national child welfare and criminology conferences. 

Center for the Study of Youth Policy University of Pennsylvania

iv

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
I. BACKGROUND AND SIGNIFICANCE 

Official statistics of child maltreatment suggest increasing rates of child 

abuse and neglect. Several studies indicate that these statistics from state CPS 

agencies underestimate the true number of children actually abused and neglected 

(NCCAN, 1998). According to the U.S. Department of Health and Human 

Services, almost 1 million children were victims of substantiated or indicated 

abuse and neglect in 1996, an approximate 18 percent increase since 1990 (Child 

Maltreatment Report, 1996). In 1990, the U.S. Advisory Board on Child Abuse 

and Neglect stated that child abuse and neglect had become an emergency; they 

unequivocally cited system failure as the cause (Gelles, 1996). 

The increase in the number of abuse and neglect reports has been matched 

by a decrease in the proportion of substantiated reports. Inquiries into the reason 

for this paradox often point to the investigative process itself as the culprit. All 

states have mandatory reporting laws and, over the last thirty years, the range of 

professionals required to report suspected child abuse and neglect, as well as the 

scope of reportable conditions, has expanded greatly. This expansion accounts, at 

least in part, for the increase in reports of child abuse and neglect. But the 

expansion also leaves the door open for inappropriate and even malicious reports 

that overtax an already burdened child welfare system. Besharov (1987) is 

convinced that unfounded reports weaken the system’s ability to respond to 

children in real danger and actively discourage appropriate reports. He repeatedly 

calls for a restructuring of the reporting system. 

Gelles(1996) points out that the manifest goals of mandatory reporting -- 

an increase in child safety, the breakdown of professional apathy and self-interest, 

the deconstruction of family privacy and the notion of children as property – are 

offset by the latent consequences – an increase in the number of reports, the 

inability of the child welfare system to handle that increase, and the corollary 

problem of unsubstantiated reports. Nationwide, at least 60% of all reports are 

unsubstantiated (NIS-3). Of substantiated cases, a full 50% never receive any 

services and are closed after investigation (National Research Council, 1998). 

Gelles suggests that better risk assessment of reported cases might solve part of 

the problem. Costin, Karger, & Stoesz (1996) agree with him and report that part 

of the problem in risk assessment is the failure of assessment techniques to 

distinguish between high- and low-risk cases. 

Lindsey and Hawkins (1994) maintain that mandatory reporting has 

transformed the child welfare system from one that serves children to one that 

apprehends their parents. They believe that the coercive authority of child 

welfare workers undermines their ability to develop positive, helping relationships 

with their clients. In discussing the failure of the system to keep children safe, 

Lindsey questions the current policy of reporting child abuse cases to public child 

welfare agencies and calls for a separation of abuse and neglect cases (1996). 

Pelton (1998) also finds the system flawed in that it links a mandate to help and 

Center for Research on Youth and Social Policy University of Pennsylvania

1

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
support families in need with an equally compelling mandate to investigate 

families and remove children. He believes that divesting child welfare agencies 

of their investigative powers would allow agencies to devote their time to the 

integration and delivery of preventive and supportive services(Pelton, 1993). 

Many experts in the child welfare field, who often do not agree with one 

another on other matters, agree with Pelton on the necessity for separating

investigations and service delivery. Together they advocate for an expanded role 

for law enforcement in the investigation of child abuse and neglect cases. 

Besharov (1990) makes the case for joint investigations between law enforcement 

agencies and child protective service workers by emphasizing the expertise police 

bring “in collecting and preserving evidence, in examining the crime scene, and in 

taking statements and confessions” (p.23). Joint investigative teams can expedite 

treatment since they approach the problem as both social, from the social work 

point of view, and criminal, from the law enforcement point of view (Garrison, 

ed., 1994). 

Orr (1999) recommends transferring responsibility for CPS investigations 

entirely to police because law enforcement officers are trained in such 

investigation and because child maltreatment is “criminal in nature.” Orr points 

out that CPS is distinct from law enforcement in that the police focus on the 

perpetration whereas child protective workers focus on the victim. More directly 

criminalizing child maltreatment would shift attention to prosecuting the offender. 

Lindsey (1996) agrees that “child abuse, like all other forms of assault is a 

criminal act, its investigation and prosecution should be transferred to the police, 

who have the training and resources to appropriately respond” (p.173). Studies 

have long shown that reports of child abuse from law enforcement agencies are 

more likely to be substantiated than those from any other source (Groenevel & 

Giovannoni, 1977). But law enforcement officers are often perceived as 

insensitive to the needs of both victims and perpetrators of child abuse. 

Consequently, many efforts to promote joint investigations, which expand the role 

of law enforcement, concentrate on sensitivity training for police investigators. In 

1997, the U.S. Department of Justice, convinced that the most effective approach 

to child abuse investigations is based on interagency coordination and planning, 

developed a training manual to help police respond more objectively and 

thoroughly to child abuse reports (NCJRS, 1997). 

Social workers, on the other hand, are often perceived as too serviceoriented, too soft on criminal abuse and negligence, and too likely to emphasize 

family preservation over child protection. This perception leads to the belief that 

joint investigative participants must be educated about the role of each profession, 

that communication and training are essential to good teamwork, but that 

treatment and prevention specialists should be separate from investigators in most 

cases (Grayson, ed., 1994). Social work has generated a large body of literature 

on the subject of child abuse and neglect. What is needed is a corollary body of 

literature generated by law enforcement (Maguire, 1993). 

Center for Research on Youth and Social Policy University of Pennsylvania

2

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Reviews of the performance of police in investigations of abuse and 

neglect are scarce. In 1991 and 1992, the American Public Welfare Association 

and the Police Foundation conducted a study of law enforcement and child 

protective service agencies. The study concentrated on developing joint 

investigation models based on innovative cooperative programs in selected 

localities (Sheppard & Zangarillo, 1996). Findings indicate that 33 states require 

joint child protective service and law enforcement investigations; 30 states 

mandate multidisciplinary treatment teams; and 40 states require CPS agencies to 

notify the police in criminal child abuse cases. Reasons cited for collaboration 

between CPS and law enforcement are: 1) to minimize the number of people 

involved in interviewing victims and families; 2) to enhance the quality of 

evidence collected; and 3) to minimize the likelihood of interagency conflict. 

The Center for the Study of Social Policy (2000) evaluated the transfer of 

responsibility for the child abuse and neglect hotline and investigation of abuse 

from the Division of Child and Family Services (DCFS) to the Family Protection 

Unit (FPU) of the state police (ASP) in Arkansas. This assessment found that 

with the new system there was confusion over the roles of DCFS, FPU, and local 

law enforcement, as well as strained relationships and poor communication 

between the units. There was tension between the local law enforcement and state 

police, who were treated as unwelcome outsiders in local jurisdictions. 

Furthermore, law enforcement officials resisted the new responsibilities as child 

protection work was seen as lacking prestige. The civilian investigators in the 

FPU, lacking full police powers, were considered of lower status therefore 

making this a position for which it was difficult to recruit and retain high quality 

staff. The Arkansas experiment also engendered community concern over a shift 

in focus to criminal process and priorities overriding child protection needs. It 

was felt that with the criminal investigation taking precedence, children and 

families might not receive necessary social services in a timely fashion. 

Furthermore, with more agencies and people involved in cases and lack of 

collaboration or coordination, the risk of children and families getting lost in the 

tangles of the complicated system increases (Center for the Study of Social 

Policy, 2000). 

Although the above-reference findings are helpful in describing current 

efforts at and challenges of collaboration between child protective services and 

law enforcement, they tend not to evaluate outcomes from these efforts beyond 

participant satisfaction surveys. What is needed now is research that goes beyond 

the descriptive to determine whether collaboration between child protective 

services and law enforcement is an effective way to increase child safety,

decrease unsubstantiated child abuse and neglect reports, and increase system

performance. 

Arguably, one of the most interesting experiments to occur in the last 

decade is the transfer of responsibility for child maltreatment investigations to law 

Center for Research on Youth and Social Policy University of Pennsylvania

3

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
enforcement, specifically the Sheriff’s Offices, in five Florida counties. While the 

immediate impetus for the Florida law enforcement experiment was the concern 

of the Legislature for child safety, the decision to transfer responsibility to 

Sheriff’s Offices was based, at least in part, on the theoretical arguments 

mentioned above regarding the separation of investigation and service provision 

in the child welfare system. One argument is that investigation is really a separate 

function and that it may be confusing to have the same agency investigating a 

case and then offering to provide service. It is also argued that investigations 

require special skills that are not typically found in public child welfare agencies, 

but are more often found in law enforcement agencies. A third argument is that 

investigations have overwhelmed public child welfare agencies and diverted their 

attention from their responsibilities in the areas of prevention and service 

delivery. Those opposing the transfer of responsibility for investigations to law 

enforcement have argued that police will be too insensitive to the needs of both 

child abuse victims and their caretakers, and that it would result in too many 

children being removed from their homes and fewer referrals for services. While 

many jurisdictions have experimented with multidisciplinary teams and expanded 

roles for police, Florida has gone further than any other state in the country in 

turning complete control of child maltreatment investigations over to a law 

enforcement agency. 

The University of Pennsylvania’s School of Social Work, through its 

Center for the Study of Youth Policy, now known as the Center for Research on 

Youth and Social Policy (CRYSP), evaluated this naturally occurring experiment 

in four of the five Florida counties (Manatee, Pinellas, Pasco and Broward) from

1990 to 2003. The study was funded by both the National Institute of Justice, the 

Office of Juvenile Justice and Delinquency Prevention, and the Florida 

Department of Children and Families. Subsequent to filing a final report on the 

study, the National Institute of Justice funded a one-year follow-up intended to 

update the findings and provide a deeper level of anlaysis. Following is a brief 

history of both the experiment itself and findings from the original study. 

Center for Research on Youth and Social Policy University of Pennsylvania

4

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
II. OVERVIEW OF ORIGINAL STUDY1

History of the Sheriff’s Office Experiment

Until recently, Florida has had a state administered child welfare system in 

which all child welfare investigations and services for its 67 counties were

delivered by a single state agency through fifteen regions and county based 

offices. Each county in Florida also has an elected Sheriff who is responsible for 

law enforcement and criminal investigations (except where there is a local law 

enforcement agency), detention and corrections, and judicial and supportive 

services. In May 1998, the Florida State legislature passed a bill that called for 

the transfer of responsibility for child maltreatment investigations the Sheriff’s 

Offices in Pinellas, Pasco, and Manatee Counties. Earlier legislation allowed for 

such transfers and the Department of Children and Families (DCF) had already 

begun to transfer investigations for high-risk cases to the Manatee County Sheriff 

in FY 1997-1998. The 1998 legislation formalized a process that required DCF to 

enter into a contract with each Sheriff’s Office for the provision of investigative 

services, and to transfer funds for that purpose, by FY 1998-1999. 

The Florida Department of Children and Families changed leadership in 

January 1999, followed by a related change in the administration of the Florida 

Abuse Hotline. A series of child deaths were attributed to the failure of DCF to 

protect the children in their charge, leaving the new administration the task of 

overhauling a child welfare system that had proved impervious to previous efforts 

at reform. The new Secretary, determined that no child should “fall through the 

cracks” of the investigative system, encouraged hotline counselors to accept more 

reports of maltreatment. The Kayla McKean Act, a piece of legislation that again 

responded to a highly visible child death, was implemented in July 1999. This 

tragic case further highlighted the difficulties DCF was having in handling child 

protective investigations. The legislation mandated that all calls from mandatory 

reporters be investigated, that a single caseworker be assigned to a case, that a 

master file be maintained by that caseworker, that local law enforcement be 

contacted on all abuse cases, that face-to-face interviews be conducted with all 

household members, and that child deaths be reviewed by committee under the 

auspices of the Department of Health. 

The impetus for this shift in responsibility was the concern of members of the 

legislature about the safety of children who were the victims of abuse or neglect, 

and about the linking of findings of abuse with the ability to prosecute the 

perpetrators. In addition to the experiment that transferred investigations to the 

Sheriffs Offices, there were parallel efforts to privatize foster care and in-home 

services and to transfer the provision of legal services to either the Office of the 

 

1

 Material in this section on Manatee, Pinellas and Pasco was culled, in part, from our initial NIJ 

report on this project (June 2003); material on Broward County was derived , in part, from our

report to the Florida Department of Children and Families (January 2003). 

Center for Research on Youth and Social Policy University of Pennsylvania

5

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
State Attorney or the Attorney General’s Office. The 1998 legislation allowed 

individual Sheriffs to conduct the investigations themselves or to subcontract with 

other law enforcement or private agencies to conduct investigations related to 

neglect cases. DCF began transferring high-risk cases to Manatee County in July 

1997 and completed the transfer of all cases by January 1998. Pinellas County 

accepted all cases in November 1999; Pasco accepted all cases in April 2000. 

Broward County, although not part of the original legislative mandate, agreed to 

participate in the transfer experiment and began accepting cases in July 1999; the 

transfer of all cases was completed in January 2000. The Sheriff’s Offices agreed 

on a common investigative protocol that was substantially different from the 

protocol used by DCF. The new protocol required civilian investigators to be 

hired by the Sheriff’s Offices as Child Protective Investigators (CPI’s) and to 

work collaboratively with either Sheriff’s Deputies, if the reported incident

occurred within the Sheriff’s Office jurisdiction or with local law enforcement 

officers if the incident occurred in a municipality with its own police force. 

Funding for the Sheriff’s Offices would continue to be provided by the State and 

passed through DCF through contracts with each Office. 

Implementation of the Experiment

Staffing and Organizational Structure 

In order to carry out the new responsibilities, each of the three Sheriff’s 

Offices created a Child Protective Investigations Section within its Operations 

Division, which is housed separately from the criminal investigations sections and 

the patrol operations (Figure 1). The primary function of these sections is to 

receive reports of abuse or neglect from the Florida Abuse Hotline, to conduct 

child protective investigations, and to make decisions regarding the allegations, 

either “verified,” “some indicators,” or “no indicators.” The sections also arrange 

for the provision of some services and prepare cases for transfer to an ongoing 

provider of services, where appropriate. A sworn law enforcement officer 

initially directed all sections. This is still the case in Manatee and Pinellas 

Counties. However, in Pasco County, the current Director is a civilian who was 

previously a DCF Administrator in Marion County. 

Figure 1. Organization of Sheriff’s Offices 

 

Deputies 

Patrol 

Operations 

Investigative 

Operations 

SHERIFF’S 

OFFICE 

Center for Research on Youth and Social Policy University of Pennsylvania

6

Crimes 

Against 

Children 

Child Protective 

Investigations

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Civilian Child Protective Investigators (CPI’s), who receive the same

basic orientation training as CPI’s employed by DCF, staff the Child Protective 

Investigations Sections of the Sheriff’s Offices. The screening and selection 

process is more rigorous in the Sheriff’s Offices than in DCF, consisting of 

background checks, polygraph tests, and psychological testing. The common 

training is provided by the Florida Professional Development Center and consists 

of an initial six-week phase followed by a second phase after cases have been 

assigned. The Sheriff’s Offices augment this training with additional training that 

is also provided to law enforcement officers. 

Detectives 

Civilians 

The number of CPI positions has increased in the Sheriff’s Offices since 

each took responsibility for investigations. As of December 31, 2001, there were 

71 CPI positions in Pinellas County, 28 in Pasco County, 23 in Manatee County, 

and 54 in Broward County. The CPI’s are organized into squads of 5 or 6, which 

are supervised either by a sworn law enforcement officer (a Sergeant) or by a 

civilian supervisor. Each Child Protective Investigations Section contains an 

analytical unit or team that initially receives the report from the Hotline, and 

prepares a case file before the case is assigned to a CPI. The case file contains the 

abuse report, prior reports, criminal history checks, provider information, 

Department of Corrections background information, and Florida Department of 

Law Enforcement (FDLE) sexual offender information. Additional staff members 

may include a training officer, Assistant Program Directors, support staff, and 

aides. 

Operation

The initial intake process at the Florida Abuse Hotline is identical

regardless of whether the investigation is conducted by DCF or by a Sheriff’s 

Office. The Hotline is centralized; if a decision is made to take a report for 

investigations, the intake information is relayed to a district DCF or Sheriff’s 

Office for assignment. Assignments are made on a rotating basis depending on 

investigator schedules. The day-to-day operation of the Child Protective 

Investigation Sections within the Sheriff’s Offices is in many ways similar to the 

investigation process in the counties where DCF conducts child maltreatment 

investigations. 

In the DCF counties, reports sent from the Florida Abuse Hotline in 

Tallahassee are routed to the unit on call and to a CPI who begins to do the 

background work. Before proceeding on initial visit to the home, the CPI may 

contact the local law enforcement agency that has jurisdiction and request that a 

Center for Research on Youth and Social Policy University of Pennsylvania

7

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
law enforcement officer be present to determine whether a criminal investigation 

is warranted. This call for assistance is at the discretion of the individual CPIs 

and therefore varies both within counties and from one county to another. The 

child abuse investigation and the criminal investigation typically proceed

independently with little coordination. The CPI is responsible for responding in a 

timely fashion, assessing the risk to the child, initiating a removal or putting 

services in place if needed, and eventually making a determination of findings 

with respect to the allegations. Figure 2 illustrates the traditional investigative 

process for the DCF comparison counties. 

Figure 2. Traditional Investigative Process in DCF Counties 

In the counties where the Sheriff’s Office is responsible for child 

altrea nties.

.

t has

boundaries. The Sheriff’s Offices have jurisdiction in all unincorporated areas. 

Call Prosecutor

Call Police

Respond to

ChildÕs Location

Assess Evidence

Arrest

Perp

Protective 

Investigator

Report from 

Hotline 

Respond to

ChildÕs Location

Assess Risk 

Remove

Child

Svcs

Needed

Criminal

Court

Family 

Court

Service

Provider

m tment there are two major differences (Figure 3) from the DCF cou

The first is that reports from the Hotline go first to the analytical team that does 

background checks and assembles a case file before the case is assigned to a CPI

The second difference is that CPI’s routinely contact the law enforcement agency 

that has jurisdiction and arrange to meet with a law enforcement officer 

immediately prior to actually conducting the visit. Local law enforcemen

jurisdiction within incorporated areas in each county, usually defined as city 

Center for Research on Youth and Social Policy University of Pennsylvania

8

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
At the joint meeting, the CPI and the law enforcement officer review the 

facts of the case and determine who will take the lead role in the initial joint 

intervie

ds, the 

s the 

s

s

g

w. If the facts indicate the possibility of criminal activity being 

associated with the report, the law enforcement officer takes the lead. If the 

report indicates that the case will be primarily concerned with service nee

CPI takes the lead. If the initial visit confirms criminal activity, the law 

enforcement officer gathers evidence to support a criminal case while the CPI 

assesses immediate service needs. The law enforcement officer then turn

criminal case over to detectives from the Sheriff’s Offices. If the CPI discover

service needs for the non-perpetrating members of the family, he or she prepare

the case for transfer to a service provider. On the other hand, it the initial visit 

confirms that there has been no criminal activity, the law enforcement officer 

signs off on the case, documenting the lack of criminality and effectively turnin

a follow-up investigation over to the CPI. As in the DCF counties, the CPI who

works for a Sheriff’s Office is responsible for removing the child from the home 

if necessary, or for putting services into place if warranted. 

Figure 3. Investigative Process in Sheriff’s Counties 

Arrest

Perp

Remove

Child

Svcs

Needed

Criminal

Court

Family 

Court

Service

Provider

Call Prosecutor

Respond to

ChildÕs Location

Assess Evidence 

and Risk

Protective 

Investigator

Report from 

Hotline

Call Deputy

Meet at

Neutral Location

to Review Case

Center for Research on Youth and Social Policy University of Pennsylvania

9

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
III. SUMMARY OF FINDINGS FROM ORIGINAL STUDIES 

The previous evaluations

2

 of the Sheriff’s Office Experiment utilized a 

quasi-experimental, pre-post design to assess changes, in both experimental and 

comparison counties, in the following areas: 

• The safety of children who are reported for abuse or neglect 

• The quality of the investigations 

• The number of children who are removed from their homes 

• The likelihood of arrest and prosecution of perpetrators of abuse 

• The services provided to children 

• The morale and credibility of the Child Protective Investigators 

• The efficiency with which investigations are conducted 

• Stakeholder support and ownership for child protective services 

The cost of conducting investigations 

• The cost of conducting investigations 

Comparison counties were selected for two reasons: 1) they were 

geographically close to the experimental counties, and 2) they were similar 

enough on selected demographic variables. The geographic proximity allowed 

researchers to use their funding more effectively as several counties could be 

visited in the course of one trip. Hillsborough was selected as a comparison 

ounty for Pinellas, Lee was selected as a comparison county for both Manatee 

nd Pasco, and Palm Beach was selected as a comparison county for Broward 

because their populations were similar and they handled approximately the same

number of investigations yearly (Table 1). 

Table 1. Demographics of Experimental and Comparison Counties 

c

a

EXPERIMENTAL Manatee Pasco Pinellas Broward 

Total Pop. 239,682 325,824 878,231 1,255,488 

% Urban 88% 59% 99% 99% 

% White 90% 96% 91% 82% 

Med. Household Income $31,416 $26,998 $30,088 $30,571 

Per Capita Income $21,584 $16,176 $22,798 $16,833 

# Children Under 18 40,813 50,204 150,820 256,272 

# Investigations 2631 3327 8366 9615

COMPARISON Lee Hillsborough Palm Beach 

Total Pop. 392,895 925,277 1,131,184 

% Urban 66% 83% 98% 

% White 91% 83% 79% 

Med. Household Income $31,904 $32,650 $45,962 

Per Capita Income $20,907 $19,129 $25,405 

# Children Under 18 65,585 191,190 215,277 

# Investigations 3537 9707 7201

Source: Census 1996; Florida DCF Annual Report 1998-99 

 

2

 Full reports can be accessed at: www.ssw.upenn.edu/crysp 

Center for Research on Youth and Social Policy University of Pennsylvania

10

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
The evaluation study conducted quantitative analyses of administrative 

000. These data were provided in five inter-related databases that required 

comple

ents, and duration of investigations. 

Pre-post analyses were conducted by experimental and comparison county pairs. 

Tab 2 nty. The 

Chi I ed data on service delivery and the

Flo a data on

crim

Tab 2

data from the Florida Abuse Hotline Information System (FAHIS) from 1995 – 

2

x data transformations to supply answers to questions regarding 

substantiation, recurrence and recidivism, severity of maltreatment, severity of 

disposition, emergency and foster care placem

le demonstrates the size of the final family datasets in each cou

ld nformation System provided limit

rid Departments of Law Enforcement and Corrections provided

inal arrest, prosecution, and disposition. 

le . Family Dataset Sizes 

 Pre Post

Manatee 2947 4001

Lee 4204 6112

 

Pasco 6901 1601

Lee 8565 2258

 

Pinellas 16,505 6308

Hillsborough 19,945 7686

 

Broward 20,117 7885

Palm Beach 14,079 6215

The quantitative analyses of administrative data were supplemented by 

analyses of primary data collected from Child Protective Investigators and Child 

eam

summarized below. 

I Child Safety

Protection T Directors, document file reviews, ride-along observations, and 

interviews with key stakeholders. The major findings from this report are 

mpacts on

• Recurrence: The rate nc ed in d Cou g

d, compa no in Pa h Cou

ce rates increas r the M e-Lee y pair, bu eased

he Pasco-Lee and Pi s-Hillsbor a

stantiated Recurrence:

of recurre e increas Browar nty durin

the post-perio red with change lm Beac nty.

Recurren ed fo anate count t decr

for both t nella ough county p irs.

• Sub Overall, substantiated rence decreased in 

e first year afte nsfer of res ity, Pa h

ounty had a lower ra recurrence within 30 days of the report 

ence rate within 60 days;

and Broward County had a lower recurrence rate within 90 days. 

recur

other counties.

3⁄4 For th r the tra ponsibil lm Beac

C te of

date; both counties had the same recurr

Center for Research on Youth and Social Policy University of Pennsylvania

11

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Of the other experimental counties, Manatee demonstrated the 

largest decrease in substantiated recurrence at 30, 60 and 90 days.

3⁄4 During the first year after the transfer, Broward County h

higher rate of recurrence prior to the lock date than Palm Beach 

County. Of the other experimental counties, only Pinellas showed 

a decrease in the rate of substantiated recurrence prior to the lock 

date, although this decrease was matched in Hillsborough as a 

comparison county. 

3⁄4 Broward County had a larger pe

ad a

rcent of families demonstrating a 

decrease in the severity of substantiated allegations and a smaller 

ho showed an increase. All other counties 

demonstrated approximately the same percentage decrease in the 

severity of the m atment allegations against families, with 

Pinellas demonstrating the smallest percentage increase. Overall, 

there was more decrease in severity among all counties than either 

increases or ma

Im cts on Perpetra

proportion of families w

altre

intenance of the status quo. 

pa tors 

alit adm tive data and the lack of data integration 

among data systems made it impossible to assess whether outcomes for 

petrator ltrea differed due to the law enforcement 

iment. There was no way to determine whether the responsible 

d to

nce involving children. There were also no significant 

ber of offenders in prison or on probation for child 

nses. However, the aggregate data did not distinguish 

between criminal sanctions that resulted from investigations by DCF or 

umber of 

perpetrators arrested or prosecuted had increased as a result of the transfer 

• The connection between child m

san

was de

• The qu y of the inistra

per s of ma tment

exper

caretakers identified in the FAHIS administrative data were arrested, 

prosecuted, incarcerated, or on probation. 

• Aggregate numbers did demonstrate that there are no major changes prepost in arrest, incarceration, or probation patterns for offenses relate

domestic viole

changes in the num

maltreatment offe

the Sheriff’s Office, and those that may have resulted from other types of

abuse investigations involving children. 

• The stakeholders that were interviewed did not believe that the n

of responsibility. 

altreatment investigations and criminal 

ctions remained unclear. The current supplemental evaluation study 

signed to explore this connection in more depth. 

Center for Research on Youth and Social Policy University of Pennsylvania

12

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Impacts on the Child Welfare System

• All county pairs increased the number of children reported as maltreated 

pre

• The sub

county- t

increas

• The average number of children placed in emergency shelters increased in 

all

number

Lee pai

either P

• Manate

volunta

Lee (in a. The average

number of children for whom voluntary services were accepted increased

ounty than in Palm Beach County. The average

number of children for whom voluntary services were rejected also rose in 

The CP

-and-post intervention.

stantiation rate for locked cases decreased in four of the five 

pairs, with on the Broward-Palm Beach pair demonstrating a sligh

e.

counties except Pasco, where there was a slight decrease. The average

of children in foster care placements increased for the Manateer, as well as the Broward-Palm Beach pair, but did not increase in 

asco or Pinellas.

e, Pasco and Hillsborough decreased the average monthly 

ry services offered by rejected, while Pinellas remained stable and 

comparison with Pasco) increased in this are

more in Broward C

both counties. 

I Perspective

CPI’s in the Sheriff-Run counties had a more positive perception of th

workload, their work environment, the trai

• eir

ning they receive, their work 

productivity, and the extent to which their organization shows concern for 

• 

• 

F CPI’s indicated they would support a transfer to law 

Ride-A

their health and safety. 

CPI’s in the Sheriff-Run counties also indicated they perceived more 

career opportunities and expected job longevity. 

CPI’s in the DCF-Run counties with longer employment times responded 

less favorably overall. 

• CPI’s in the Sheriff-Run counties saw their role as “counselor”, while 

those in the DCF-Run counties saw it as “child protector”. 

• Almost half the DC

enforcement in their own counties. 

long Observations

Center for Research on Youth and Social Policy University of Pennsylvania

13

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
• Ride-along observations with CPI’s in all counties revealed that Broward, 

at least in this very small sample, did not perform as expected given the 

.

Pinellas proved more compliant with proscribed protocol than the other 

r was there a difference in attitude toward the families 

involved in investigations. 

 

Case F

procedures originally established by the Broward County Sheriff’s Office

•

experimental counties. There was no difference in law enforcement 

involvement in investigations between experimental and comparison 

counties, no

ile Reviews

Improvements in case file completeness as well as the completeness of the

forms themselves were ev

• 

ident in all counties at some point over the study 

period, but the improvements did not seem to be associated with the law 

• 

Implem

enforcement intervention. 

The majority of cases declined for prosecution are labeled “lewd and

lascivious”, with the reasons to decline a case for prosecution are usually 

given as “no evidence,” “no interview,” or “no witnesses.” 

entation Issues

uration of investigations increased for all maltreatment types 

in all counties, with the exception of a decrease in Lee (as compared with

• 

las show that the turnover rates were higher than 

their comparison counties in 2000, but lower than the comparison counties 

• Manatee outperformed all DCF counties on the cost of the investigation, 

under dispute.

Oth S

• The average d

Manatee) in the duration of investigations for threatened harm cases. 

Staff turnover data were not available for Pasco County. However, data 

from Manatee and Pinel

in 2001. 

but the figures from Pasco and Pinellas make a cost comparison difficult, 

as their interpretation is

er takeholder Perspectives

• Child Protection Teams in the experimental counties uniformly agreed that 

ever, indicated a slight preference for 

working with DCF. 

• dges in the Pasco and Pinellas expressed satisfaction with the 

improvements in investigations after the law enforcement transfer. The 

judge in Manatee, who initially expressed concerns, was unavailable for 

their relationship with the CPI’s in the Sheriff’s Offices had improved 

over time. Survey respondents, how

Ju

Center for Research on Youth and Social Policy University of Pennsylvania

14

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
comment at the end of the study. One judge in Palm Beach County was 

concerned about the quality of investigations of more serious abuse and 

sexual abuse cases. Representatives from the Office of the Attorney 

General and the Palm Beach Sheriff’s Office wanted to see more 

• ed

ter the 

he Manatee attorney, who was interviewed at 

the beginning of the study, felt it was too soon to tell if the transfer was 

ll attorneys believed it would have no impact on arrest and 

prosecution. 

• 

ir

on counties.

ith

Overall, our findings indicated that the law enforcement experiment has 

l as its proponents had hoped. Changes in recurrence, 

bstantiation, emergency shelters, and foster care placements proved to be 

neg i

countyboth co

tervention came from the other community stakeholders in all experimental 

countie

compar

 

Limita e Original Study

communication between their offices and DCF. 

Staff of the State Attorney’s Office in both Pasco and Pinellas express

the same satisfaction with the improved quality of investigations af

law enforcement transfer. T

successful. A

Service providers were generally satisfied with their relationships with 

CPI investigators in the experimental counties, but the same is true of the

relationships in the comparis

• Law enforcement officials and legal service providers were satisfied w

their working relationships in Manatee, Pasco and Pinellas. 

not proved as successfu

su

lig ble across counties. Comparisons between experimental and comparison 

pairs demonstrated that when change did occur, it usually occurred for 

unties. The strongest evidence in support of the law enforcement 

in

s and from the Child Protective Investigators (CPI’s), even in the 

ison counties.

tions of th

system

Does tr

f law enforcement taking responsibility for investigations? The most that could 

e changes over time there seems to be no 

 was the complexity of the 

dm

Prepara

leaving

significant change. A tertiary problem 

periods for the experim parison county pairs, as well as the relatively 

sho lem made 

inte re

One of the study’s limitations was the lack of data integration across 

s, making it impossible to answer one of the primary research questions: 

eatment of perpetrators differ with regard to criminal sanctions as a result 

o

be established is that in aggregat

association with the intervention. A secondary problem

a inistrative data and the time needed to prepare the data for analysis. 

tion of the FAHIS data absorbed the much of study’s time and resources,

little time to conduct the type of rigorous analyses capable of detecting 

was the differential lengths of pre-post 

ental-com

rt post periods for three of the four experimental counties. This prob

rp tation of findings particularly difficult. 

Center for Research on Youth and Social Policy University of Pennsylvania

15

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
IV. 

l

study a m the

origina

Res rc

CURRENT SUPPLEMENTAL STUDY 

The current study is designed to supplement findings from the origina

nd to further explore under-examined or unanswered questions fro

l study.

ea h Questions

The question of child safety was answered preliminarily by the first study, 

h the time and data limitations precluded certain types of rigorous 

s. The current study therefore proposed additional data collection and 

althoug

analyse

secondary analyses to answer the question with more certainty. These analyses 

ill also be used to further determine the effect of the experiment on system

per m

e adequately addressed in the

revious study was “What happens to the perpetrator of serious child 

mal a

Sheriff kely to be

rrested or prosecuted. This seemed like a plausible hypothesis given the 

assump

e Child

and

 The organizational culture in the Sheriff’s Offices might support the arrest 

ild maltreatment offenders more than the 

DCF culture

ore

w

for ance. 

A major research question that could not b

p

tre tment?” The study wanted to find out whether in the counties where the 

’s Office conducts the investigations, perpetrators are more li

a

tions that in the experimental counties: 

 Child Protective Investigator’s would receive more training in 

investigative techniques and collecting evidence

 There would be closer coordination and communication between th

Protective Investigators and those who conduct criminal investigations

the State Attorney’s Office 

and prosecution of serious ch

The question of the extent to which the perpetrators of serious child 

maltreatment are arrested, prosecuted and incarcerated – and what the alternative 

outcomes are if they are not arrested, prosecuted and incarcerated -- remains an 

important one. The current study proposes to explore these questions in m

depth with the Broward County Sheriff’s Office and the Broward County State 

Attorney’s Office. 

 

Design

The current study is designed to supplement findings from the original 

study and is structured to accommodate changes in the Florida data system. There 

was a gap of approximately one year between the end of the original project and

the start of the current supplementary project. In that year, Florida implemented a 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
new data system, Home Safe Net, an Access-based data management system, 

hich replaced the FAHIS system. This change influenced the study design in 

two wa

e

systems were amenable to integration. Because the new system

was im emented in September 2002, however, supplemental data could still be 

engthen the post periods for the experimental counties, 

vercoming one of the limitations of the original study. Second, the new data 

system

riminal 

analytic dataset by: a) adding data from 2001 and 2002 to extend 

ost-periods for the experimental counties; b) adding data from an additional 

compar ta

hensive

pose of

outcomes for perpetrators through 

n exploration of the criminal court data and an attempted link between court and 

chi c) explore

possibi n the two systems. The 

third purpose of the study is to examine the operation of the new Florida child 

we

dy is primarily secondary data analysis of 

xisting and supplemental administrative data with an emphasis on data 

inte

outcom ion,

severit The data integration protocol is exploratory, focusing on the 

eoretical possibilities for integration based on the implementation of a pilot 

protoco s of

ss 

e variables identified by the State. 

w

ys. First, the data needed to supplement our original data could be 

provided only for dates prior to the implementation of the new data system, as th

older and newer

pl

provided that would l

o

allowed for easier record review and facilitated the manual search

necessary to create a data integration protocol between child welfare and c

court data. 

The purpose of the current study is to first create a larger and more 

comprehensive

p

ison county (Sarasota) to increase comparative power; and c) merging da

from the two previous studies with the additional data into one compre

dataset that can be subset for more discrete analyses. The additional data work is

needed to answer some of the original research questions on a deeper level 

through more rigorous analyses of the administrative data. The second pur

the study is to: a) create a protocol for tracking

a

ld welfare data; b) implement the protocol and analyze results; and,

lities for institutionalizing data integration betwee

lfare data system, Home Safe Net (HSN). 

The design of the current stu

e

gration within and between data systems. The quantitative analyses focus on 

e measures related to the law enforcement experiments, e.g. substantiat

y, recidivism.

th

l. This exploration will also provide a frequency distribution analysi

the court data and significance testing of associations between cases presented to 

the court and those accepted for prosecution. The examination of the new child 

welfare data system will address the strengths and limitations, and allow for a 

comparison of the performance of the Sheriff’s counties with other districts acro

the state on outcom

Methods

To achieve the first study objective, it was necessary to first retrieve and

integrate additional child welfare administrative data (FAHIS) to lengthen the 

post periods in the experimental counties. The Florida Department of Children 

and Families provided additional data through August 2002, although it became 

Center for Research on Youth and Social Policy University of Pennsylvania

17

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
necessary to drop the 1995 data due to slight but crucial differences in data 

maintenance at the State level. The final dataset therefore includes reports on 

child maltreatment from 1996 through August 2002, which did accomplish

objective of lengthening post periods while maintaining adequate pre periods. 

The additional data were provided, as in the original study, in five inter-related 

databases, requiring another set of complex transformations before integrating 

older and new data. 

The attempt by the original study to integrate court data and child w

data had proved unsuccessful, necessitating a new approach to accomplishing the 

second obje

the

elfare

ctive and third objectives. Being familiar with the new Home Safe 

Net (HSN) data system, the Broward County Sheriff’s Office (BSO) suggested 

that it w

nty

ed,

To accomplish the fourth objective, the study reviewed a series of statewide re

e; and b)

 

ould be easier to track back from the criminal court data to their new 

system than forward from their system to the court data, and much easier than 

trying to use the old and new data systems simultaneously. The Broward Cou

State Attorney’s Office subsequently provided data on criminal prosecutions for 

child maltreatment from 2001 through 2003 and the BSO agreed to assist in 

searching for a random sample (N=25) of these cases in Home Safe Net. The 

purpose of the search was to estimate how many cases the two systems shar

how cumbersome and time-consuming the search is without unique identifiers, 

and how easy it would be adapt or modify one or both systems to make this 

information more readily available to child welfare workers. Everyone 

anecdotally agrees that it would be useful to know which dependency cases are 

accompanied by parallel criminal cases so that family interventions can be crafted

appropriately. 

ports generated by the new data system to: a) describe the new child 

welfare data collection system from a strengths and limitations perspectiv

compare the performance of the Sheriff’s counties with other districts across the 

state on outcome variables identified by the State. This review presents a current

impact picture to complement the retrospective impact picture provided by 

quantitative analyses. 

 

For purposes of clarity, the following report is divided into three sections:

1) Criminal Court Data and the Link to Child Welfare; 2) Secondary Data 

Analyses of Child Welfare Data, 1996 - 2002; and 3) Performance of Sheriff’s

Offices in Child Maltreatment Investigations. 

Center for Research on Youth and Social Policy University of Pennsylvania

18

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
V. CRIMINAL COURT AND THE LINK TO CHILD WELFARE 

A. OVERVIEW

As discussed in the introduction to this report, the previous evaluation of

the impact of transferring child maltreatment investigations to the Sheriff’s 

Offices was not able to determine whether perpetrators of child maltreatment 

ere more likely to receive criminal sanctions as a result of the transfer. The 

O)

d

nd results

SAMPLE DESCRIPTION 

or

with

sequently used to search the BSO database. Of those 

ses with names, 111 were also disposed. Significance testing was done to 

nd

Table 3 demonstrates that there is a significant correlation between names 

being attached and their dispositions status, which is to be expected and 

unavoidable given the exclusion criteria. With regard to differences between 

disposed and non-disposed cases, race and sex are not significant, although there 

are more white females in the disposed cases. The degree, type and class of the 

charge are significantly associated with disposition, which is not surprising. The 

majority of disposed and non-disposed cases fall into the category of third degree 

abuse felonies; percentages in the disposed cases are smaller and represent a 

w

reason for the inability to answer that particular research question was the lack of 

data integration between the criminal court and child welfare systems. The 

evaluation suggested that closing the gap between the two systems would be 

desirable. Both child welfare and court administrators, when questioned, agreed

that such integration would be important in terms of family treatment options.

To examine the link between criminal court and child welfare, and to 

establish a protocol for institutionalizing the link, the current study first collected

data on child maltreatment cases presented to the State Attorney’s Office (SA

in Broward County for prosecution in 2001 through 2003. These data were use

to search the Broward Sheriff’s Office (BSO) Home Safe Net records from the 

same time period to determine the degree to which the two datasets matched in 

terms of identified perpetrators. Following are the results of the initial SAO

criminal court data collection process and outcomes, as well as process a

of the BSO search. 

B.

The sample for the study consisted of 1127 cases presented to the SAO f

prosecution consideration from 2001 through 2003. Of those cases, 143 were

eventually accepted and disposed. To protect the privacy of the defendants, the 

SAO did not include defendant names in the sample if the case was still pending,

if the case had been rejected for prosecution, or if the perpetrator was a juvenile. 

Defendant names were provided for 235 of the 1127 presented cases. Cases

names attached were sub

ca

assess whether there was a correlation between a name being present and a case 

being disposed, and whether there were any differences between disposed a

non-disposed cases with respect to relevant variables. 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
significant difference. Finally, the length of time between arrest and disposition is

lso significantly associated with disposition status. 

able 3. SAO Original Sample (N=1127) 

a

T

 Presented/

Disposed Percent 

Presented/

Not 

Disposed 

Percent Significance 

Test 

Significance 

Level 

Number of Cases 143 12.7% 984 87.2% 

Names Attached 112 78.3% 124 12.6% r=.533* 0.000 

Age (mean years) 34.6 35.35 

Race (white) 52 59.1% 448 45.7% 

Sex (female) 68 53.5% 458 47.1% Impact on Being Disposed 

Degree of Charge (3rd

degree) 88 69.8% 826 83.9% chi=18.68 

(df=3) 0.000 

Type of C

3r 0.000 harge (abuse,d degree) 67 46.9% 600 61.0% chi=40.90 

(df=6)

Class of Charge (felony) 96 76.2% 908 92.3% chi=33.46 

(df=1) 0.000 

Lag between Offense & Arrest 

Mean (months) 0.97 0.33 F=2.13 0.000 

Category: 1 month or

under 104 87.4% 459 46.6% chi=13.46 

(df=3) 0.004 

The data sent to BSO for tracking back through their child welfare data 

cluded all cases from the original SAO data with names attached (N=235). 

Table 4 ignificant differences between 

isposed and non-disposed cases. The search sample differs from the original 

sample

ss

in

 describes the search sample, comparing s

d

in that age and race are significantly associated with disposition, while the 

type of charge and time between offense and arrest are not. The degree and cla

of the charge remain significant. 

Table 4. BSO Search Sample (N=235)

 Disposed Percent Not 

Disposed Percent Significance Test 

Significance 

Level 

Number of Cases 111 47.2% 124 52.8% 

Age (mean years) 34.6 32.2 F=3.84 0.051 

Race (white) 42 37.8% 64 51.6% chi=4.49 

(df=1) 0.023 

Sex (female) 60 54.1% 69 55.6% 

Degree o

degree) 0 f Charge (3rd 76 68.5% 91 73.4% chi=31.12 

(df=9) 0.00

Type of Charge (abuse, 3rd 

degree) 59 53.2% 41 33.1% 

Class of Charge (felony) 83 74.8% 109 87.9% chi=6.7.5 

(df=1) 0.007 

Lag between Offense & Arrest

Mean (months) 1.04 0.42 

Category: 1 month or under 93 86.9% 118 95.2% 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 5 compares the characteristics of the disposed cases in the SAO 

ataset (N=143) with the disposed cases in the BSO dataset (N=111) in terms of 

and l t in place. Over half the 

disposed cases in both ted in a plea referred to as “nol ”

nown as “no contest.

” plea me hat enda

d

sanctions ength of time until sanctions are pu

sets resul

”

o as charged , also 

k

A “nolo ans t the def nt does no

e it either utti h such a plea, a defend ees that h

und guil the co with er ad g guilt to the 

resented. Defendants are likely t this hen

victed wis oid a trial p

il pro ution havi e sa c cing a

3 mbination of this plea and guilty pleas accounts for over 80% 

e SAO ta us this and e

fferen in pe ge other

 neg

Tab es for Disposed Cases (N=143)

t admit the charge, but 

does not disput

or she may be fo

. In p ng fort ant agr e

ty by urt out ev m tin

plea w

it

charges as p o use they feel they 

are going to be con a also forestalls

the possibility of civ

and h to av jury . This le

sec while ng th me effe t on senten s a

guilty plea. The co

of dispositions in th da ed for study for ov r 90% of

dispositions in the BSO search data. 

variables appear to be

Di ces rcenta s among

ligible. 

le 5. Outcom

DIPSOSED CASES SAO

Original Percent BSO Search Percent 

Number of Cases 143 111 

Disposition 

Pled Guilty as Charged 39 27.3% 36 32.4% 

Pled Nolo to Charges 80 55.9% 75 67.6% 

Probation 114 98 

Mean (years) 2.8 3 

Category: 2-4 years 61 53.5% 57 58.2% 

Sentence 35 33

Mean (months) 4.9 6

Category: Under 6 months 15 42.9% 14 42.4%

Lag between Offense and Arrest

Mean 1.2 1.0 

Category: 1 month or under 104 87.4% 93 86.9%

Lag between Offense & Disposition

Mean (months) 9.5 9 

Category: 6 months or under 54 37.8% 46 41.4%

Lag between Arrest & Disposition

Mean (months) 8.5 8

Category: 6 months or under 61 43.9% 51 46.3% 

 

3

 http://www.wordiq.com/definition

Center for Research on Youth and Social Policy University of Pennsylvania

21

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
C. RESULTS: TRACKING BACK FROM CRIMINAL 

DISPOSITION TO ORIGINAL REPORT 

Constructing The Final Search Sample 

Figure 4 illustrates the protocol used to construct a final dataset 

contain 28 cases of child maltreatment that resulted in criminal arrest, 

prosecu

data,

ing 1

tion, and sanctions. BSO reports were found by matching names first, 

then by SAO offense date. If a BSO report with the same name had an offense 

date that was more than one month before or after the report date in the SAO

it was not included as a match. Of the 235 names provided, BSO found 128 

matching reports in their Home Safe Net database. Of the unmatched reports, 45

had no name match and 62 had no offense date match. Following is an analysis 

of the differences between the original sample and the search sample. 

Figure 4. Data Tracking Protocol and Results 

SAO-BSO Search Sample (N=235)

SAO Original Data (N=1127)

BSO Reports Found (N=128)

SAO O Me ed

=128) 

 and BS rg

(N

No Name (n=45)

No Date (n=62)

Reports Not Found (N=107)

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Analysis of Reports Found and Not Found

 reports found (N=128) with those not 

found (N=107). Chi-square and means testing revealed no significant differences 

betwee esults are

Table 6 compares characteristics of

n to two groups of cases for any of the relevant variables. These r

encouraging because they indicate that an analysis of reports found may be

representative overall of the entire search sample. 

Table 6. Comparison of Reports Found and Reports Not Found 

 Found Percent Not 

Found Percent 

Number of Cases 128 54.5% 107 45.5% 

Cases Disposed 64 64 

Age (mean years) 33.8 32.7 

Race (white) 58 45.3% 48 44.9% 

Sex (female) 64 50.0% 65 60.7% 

Degree of Charge (3rd degree) 93 69.2% 74 72.7% 

Type of Charge (abuse, 3rd degree) 60 46.9% 40 37.4% 

Class of Charge (felony) 105 82.0% 87 81.3% 

Lag between Offense & Arrest (mean months) 0.71 0.71 

Disposition 

Pled Guilty as Charged 19 29.7% 17 36.2% 

Pled Nolo to Charges 45 70.3% 30 63.8% 

Probation (mean years) 3.3 3 

Sentence (mean months) 7.1 5.2 

Lag between Offense & Disposi

months) 10.2 tion (mean 8.6 

Lag between Arrest & Disposition (mean 

months) 7.71 9.13 

Analysis of Reports Found by Disposition Status

For the reports found, BSO provided information on allegations, findings, 

and relationship between perpetrator and child. When the SAO and BSO data 

were merged, a final sample (N=128) provided data from allegation through court 

disposition and sentencing. Table 7 demonstrates the differences in the reports 

found by disposition status on demographics, aggregate allegations, and aggregate 

findings. Chi-square and means testing revealed no significant differences 

between the disposed and non-disposed cases, suggesting that these variables play 

no significant part in whether a case is accepted for prosecution. These results are 

also encouraging because they indicate that an analysis of disposed cases may 

apply to the non-disposed cases as well. 

Center for Research on Youth and Social Policy University of Pennsylvania

23

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 7. Comparison of Disposed and Non-Disposed Cases in Found 

Reports

BSO Matched Data Disposed Not 

Disposed

Number of Cases 64 64 

Age (mean) 34.1 33.5 

Race 

White 26 32 

Black 38 32 

Sex 

Female 32 32 

Male 32 32 

Total Number Allegations 150 165

Mean # Allegations per Report 2.35 2.67 

Total Number of Findings 90 98

Mean # Findings per Report 1.47 1.56

mation on the number and type of initial 

a e of findings, rela p be n th

p maltreatmen , and etra

Each BSO report indicated 1-5 types of 

Allegations and findi o par latio ip be he

mean number of allega th ean r of ings ort

( nship proved significan =4.78, <.001). As intuitively 

expected, the allegations and findings are correlated.

Figure 5. Comparison of Mean Number of Allegations and Findings 

BSO also provided infor

llegations, the number and typ the tionshi

t c se

twee e

erpetrator and the child involved in the tor

allegations and 1-4 types of findings. 

a perp s. 

ngs were aggregated t com e the re nsh tween t

tions per report and e m numbe find per rep

Figure 5); the relatio t (F

1.

an

5

0

0.5

1

Disposed Not Disposed

2

2.5

3

me

# Allegations per

Report

# Findings per

Report

Disposed, r=.483 <.01; Not Disposed, r=.256, <.05 

Figure 6 illustrates the differences in type of allegations by disposition

status. The majority of all cases involve an allegation of physical abuse; more of 

Center for Research on Youth and Social Policy University of Pennsylvania

24

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
those cases are disposed than not disposed. The same is true for allegations of 

tively even. None of these differences proved to 

e significant.

Figure 6. Types of Allegations (N=323) by Disposition Status 

family violence and hazardous conditions, while the distribution between 

disposed and non-disposed cases with other allegations -- substance related and

inadequate supervision -- is rela

b

0

to

20

40

60

80

100

120

Substance

Related

Inadequate

Supervision

rd

Conditio

ns

tal n

u r

Physi

Sexu

cal

al

Haza ous

F

Vi

am

olen

ily

ce

mbe

Disposed

Not Disposed

Figure 7 reports the distribution of types of findings by dispositio

The fact that a greater number of allegations with verified findings are not

disposed than are disposed is surprising, as is the fact that there are so many ca

with no findings that are disposed. This situation is complicated by the fact th

some of the findings in a report may be verified, while others are not. 

 

Figure 7. Findings (N=188) by Disposition Stat

n status.

ses

at 

us

0

10

20

30

40

50

60

70

Verified Some Findings No Findings

total n

u

m

be

Disposed

Not Disposed

o further explore the situation, the findings were recoded dichotomously 

as subs d.

the number of the total findings that were substantiated. This recoding transposed 

T

tantiated or not substantiated, with “some findings” coded as substantiate

Each report was further coded with the total number of findings for the report and

Center for Research on Youth and Social Policy University of Pennsylvania

25

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
the total number of 188 findings to a report-based code that established the 

substantiation status for each of the 128 reports.

As Table 8 demonstrates, 79.6% of all reports (N=102) substantiated all 

their findings. Of those reports with only substantiated findings (N=90), the 

majority (70.3%) consisted of one finding only. Of the reports with all 

posed.

onversely, 65.4% of cases with split findings (N= 26) were disposed. There was 

only one report with no substantiated findings; it was not disposed. 

Table 8. Reports by Substantiation Status (N=128) 

substantiated findings (N=47), less than half of them (46.1%) were dis

C

 Disposed Not Disposed

Reports w/All Sub Findings Number Percent Number Percent % of Total

1 42 46.7% 48 46.7% 70.3% 

2 3 50.0% 3 50.0% 4.7% 

3 1 33.3% 2 66.7% 2.3% 

4 1 33.3% 2 66.7% 2.3% 

Total w/All Sub Findings 47 46.1% 55 53.9% 79.7%

Reports with Split Findings 17 68.0% 8 32.0% 19.5%

Reports with No Sub Findings 0 0.00% 1 0.8% 0.8%

Finally, Figure 8 illustrates the relationship between perpetrator and child

in reports found. The majority of all cases involve mother as perpetrator.

owever, a smaller percentage of these cases are disposed than not disposed. 

are fewer step-parents involved as perpetrators overall, fewer of 

well as other relative

nd non-relative caretakers, are represented more in disposed than non-disposed 

cases. None of the relationships are significant in their association with disposed 

and non-disposed cases.

Figure 8. Relationship between Perpetrator and Child 

H

Although there

them are disposed. Conversely, fathers and paramours, as

a

0 5 10 15 20 25 30

Father

Mother

Step-parents

Paramour

O ther

total number

Not Disposed

Disposed

 

Center for Research on Youth and Social Policy University of Pennsylvania

26

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
With regard to types of criminal charges (Figure 9), over 50% of all

involved simple abuse charges; 64.1% of all disp

cases

osed cases involve this type of

charge. The relationship between disposition and type of charge is statistically 

signific

e

sposed

igure 9. Type of Criminal Charge by Disposition Status

ant (<.006). The second highest percentage of cases involves neglect 

without great harm; only 12.5% of those cases are disposed. With regard to th

degree of the charge, Figure 10 reveals that in both disposed and non-di

cases 70% of the charges are third degree felonies. 

F

0

10

20

30 r

40

50

buse Abu

Neg

Gr

Har

Neg

G

H

total numbe

Abuse Agg A se &

lect,

eat

m

lect, No

reat

arm

Disposed

Not Disposed

 i=12.71 (df=3) <.006 

Figure

ch

10. Degree of Criminal Charge by Disposition Status

0%

10%

20%

30%

40%

50%

60%

70%

80%

Misdemeanor Felony, 1st and 2nd Felony, 3rd degree

degree

Disposed Not Disposed

To explore the association between charge type and degree, and their 

relationship to disposition, types of charges were dichotomized. The first three 

charge types were coded as abuse and serious neglect, and the fourth charge was 

coded as simple neglect. When tested, the relationship of the two to disposition 

proved significant only with regard to 3rd degree felony charges (Figure 11). 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 11. Type and Degree of Charge by Disposition Status

0

8

Abuse &

Serious

Neglect

Simple

Neglect

Abuse &

Serious

Neglect

Simple

Neglect

Disposed Not-Disposed

Misdemeanor

Felony, 1st & 2nd

Felony, 3rd*

16

24

32

40

chi=8.98 df=1 <.003 

Analysis of Disposed Cases

Ultimately, the study was able to track 64 cases from allegation through 

criminal prosecution outcome. Table 9 provides a snapshot of the sample in 

terms of demographics and aggregate allegations, findings, charges, sanctions and 

ses

Number of Cases 64 

case duration. 

Table 9. Distribution of Relevant Variables in Disposed Ca

Age (mean) 34.1 

Race (white) 26 

Sex (female0) 32 

Total Number Allegations 150

Mean # Allegations per Report 2.35 

Total Number of Findings 94 

Mean # Findings per Report 1.47 

% Charged w/Abuse & Serious Neglect 87.5 

% Charge w/ 3rd Degree Felony 71.9 

% Pleading Nolo 70.3 

% Probation 2-4 years 54.5

% Sentenced over 1 year 47.4 

Avg Time Between Offense & Arrest (mos) 1.03 

Avg Time between Arrest & Disposition (mos) 7.71

Avg Time between Offense & Disposition (mos) 8.6 

Figure 12 illustrates that the majority of cases (70.7%) prosecuted had 

riginal allegations involving physical abuse. Of all allegations, 52.2% were 

erified. Figure 13 illustrates a comparable majority of cases (59.4%) being 

riminally charged with 3rd degree felony abuse. The relationship between the 

pe of criminal charge and the degree of the charge proved significant 

hi=67.04, df=6, <.000).

o

v

c

ty

(c

Center for Research on Youth and Social Policy University of Pennsylvania

28

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 12. Distribution of Maltreatment Allegations* by Type 

70.7%

8.7%

8.0%

3.3%

9.3%

Physical

Substance

Related

Inadequate

Supervision

Hazardous

Conditions

Family Violence

* 52.2% of all allegations substantiated

Figure

also allowed for an exploration of the types of criminal 

s d maltreatment perpetrators. Of the 64 disposed cases, 

5 d 19 received son or jail sentence. Only 3

c t all; 13 cases received both probation and sentence 

t ip between probation and sentence was significant 

(chi=13.43, df=6, <.037). 

inal sanctions imposed by the type of 

c t in the case of

significant in the case of sentencing 

Figure in

13. Distribution of Criminal Charges by Type and Degree 

4.7%

1.6%

12.5% Abuse, 1st and 2nd

Abuse, 3rd degree

59.4%

3.1%

Agg Abuse, MM

Agg Abuse, 1st or 2nd

18.8%

Serious A or t or

2nd

N, 1s

Neglect, 3rd degree

The merged data

anctions imposed on chil

5 received a probation sanction an a pri

ases received no sanctions a

ime. The relationsh

When comparing the type of crim

riminal charge, a relationship between the two proved significan

probation (chi=14.74, df=6, <.022), but not

( 14). It is clear that most prosecuted cases of child maltreatment result

4 months or less of probation and/or more than six months of a jail sentence. 

Center for Research on Youth and Social Policy University of Pennsylvania

29

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 14. Relationship between Criminal Charge and Criminal Sanction 

0

5

10

15

20

25

30

under 4 4 and over under 6 6 and over

Probation*

(years)

Sentence

(months)

Misdemeanor

Felony, 1st or 2nd

Felony, 3rd

* chi=14.74 (df=6) <.022 

To complete a picture of the link between criminal court and child welfare 

ata, Table 10 demonstrates the report distribution from allegation to 

Table 10. Report Distribution from Allegation through Sanctions

d

substantiation to criminal charge to criminal sanction. 

Reports by Allegations (N=87) Number 

Physical Allegations 48

Inadequate Supervision & Substance-Related 21 

Hazardous Conditions & Family Violence 18 

Reports by Findings (N=64) Number 

All Sub Findings 47 

Split Findings 17 

No Sub Findings 0

Reports by Criminal Charges (N=64) Number 

Abuse, 1st or 2nd 3 

Abuse, 3rd 38 

Agg Abuse, MM 12 

Agg Abuse, 1st or 2nd 2 

Serious A or N, 1st or 2nd 1 

Neglect, 3rd 8 

Reports by Criminal Sanctions: Probation (N=40) Number 

Probation, under 4 years 28

Probation, 4 years and over 12

Reports by Criminal Sanctions: Sentence (N=19) Number 

Sentence, under 6 months 6 

Sentence, 6 months and over 13 

Figure 15 illustrates the distribution of perpetrator-child relationship in 

e disposed cases. Although the previous analysis of these relationships by 

isposition status demonstrated that a higher percentage of found reports with 

th

d

Center for Research on Youth and Social Policy University of Pennsylvania

30

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
fathers as perpetrators were disposed than those with mothers as perpetrators, this 

nalysis of the relationships in the total disposed cases demonstrates that mother 

perpetrators are in the majority (39.1%). These relationships were not 

significantly associated with either probation or sentencing. 

Figure 15. Distribution of Perpetrator-Child Relationships 

a

3.1%

6.3% 6.3%

14.1%

31.3%

39.1%

O ther

Related

Stepfather Other Not

Related

Paramour Father Mother

for the merged SAO/B e tracked, a little

over half of the reports we

disposed and all had at least one substantiated allegation in the report. There were 

87 allegations contained in the found reports and over 70% of them yielded 

c Over 70% of these cases received criminal 

s

Figure 16 on the following page illustrates the results of the tracking 

protocol and makes clear that

re found. Of those that were found, half had been 

SO sampl

harges in a criminal case. ultimately

anctions.

Center for Research on Youth and Social Policy University of Pennsylvania

31

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 16. From Child Welfare Report to Criminal Court Sanctions 

Reports Searched: 235

Disposed Reports with 1 or more

Substantiated Allegation: 64 (100%)

Disposed Reports Found: 64 (50%)

Disposed Reports with

Substantiated Allegations 

resulting in Criminal Charges: 

64 (73.6%)

Probation (40)

Sen nce (19)

Overlap (13)

D. SUMMARY OF FINDINGS ON THE LINK BETWEEN 

CHILD WELFARE AND CRIMINAL SANCTIONS 

The findings from the tracking project are limited to some extent by the 

existence of significant differences between the SAO original and the BSO search 

sample, making the search sample less than representative of the whole. These 

differences are not easily explained because there were multiple criteria involved 

in the decision to exclude names from the original sample. It is impossible to 

determine how many of the cases without names would have been located in the 

te

Disposed Reports with

Criminal Charges 

resulting in Criminal

Sanctions:

46 (71.9%) 

Reports Found

Receive 

Sanctions: 

35.9%

Mean # 

Months

from

Initial

Report to

Sanctions:

8.6

Reports Found: 128 (54.5%)

# Allegations in Disposed Reports: 

150 in 87 Reports 

Center for Research on Youth and Social Policy University of Pennsylvania

32

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
BSO search had names been provided and, if they had been, how they would have 

The lack of significant differences between the disposed cases in the SAO 

original sample and the BSO search sample indicate that the impact of being able 

to include the no names in the search would probably have been negligible. 

Therefore, the findings on criminal sanctions for child maltreatment perpetrators 

from the search sample may be considered representative of the larger sample. 

This statement is supported by the lack of significant differences on all relevant 

variables between the reports found and not found in the search sample. 

Findings are limited as well by the fact that there is no way to determine 

that the match between criminal case and child welfare report is exact. However, 

the inclusion criteria for the match are stringent enough to feel confident the 

matches are accurate. Also, matching the multiple allegations and findings from

the BSO child welfare data with the single case specific outcomes in the SAO 

data precludes exact matching of allegation, finding, charge, disposition and 

sanction. However, collapsing allegations and findings into dichotomous units 

allowed for an approximation of one-on-one matches with the corresponding 

criminal case. Although the matches remain somewhat less than precise, the 

analytic findings are robust for an essentially exploratory study of the link 

between child welfare and criminal sanctions. 

Within the search samples, type of allegation and relationship to the child 

did not prove significantly different for disposed cases. The type and degree of 

charge were not related to disposition when analyzed separately, but were 

significantly related when collapsed and combined into a single variable. 

Disposed cases consisted primarily of substantiated allegations of physical abuse 

resulting in 3rd degree felony charges. Almost one-third of disposed cases 

resulted in either probation or a jail sentence, although only the relationship 

between probation and the degree of the charge proved significant. The most 

commonly reported relationship in the disposed cases was between mother and 

child. None of the relationships, however, were significantly associated with 

pecific probation or sentence time. 

Discussion

affected disposition and criminal sanctions. 

s

received crimin n

the par f pros to treat 

child m

Overall, only 35.9% of reports found through the tracking protocol 

al sanctions. This low figure may be the result of reluctance o

t o ecutors – and perhaps child welfare investigators as well –

altreatment as a criminal offense. If the child welfare and criminal 

systems were more interactive, this reluctance might be overcome. If there was 

more acknowledgement of the impact of perpetrators within the family dynamic, 

there might be alternative treatment plans developed for families with a cooccurrence of dependency and criminal cases. 

Center for Research on Youth and Social Policy University of Pennsylvania

33

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Creating a feedback loop between the two systems would be the first step 

in what would optimally be a data integration process. Discussion with the 

roward County Sheriff’s Office (BSO) revealed that they are willing to 

particip

r to

e

atekeeper would not initially have access to the criminal files, as the State 

Attorne

n

and

is

t, as

d feedback loop. The BLACK

nes indicate the current state of one-way transfer of data from the investigator to 

the cas

eper

and

B

ate in a pilot that would create the feedback loop between BSO and 

criminal court if the pilot were funded to the extent necessary to dedicate a staff 

member as gatekeeper on the issue. The BSO would instruct each investigato

note in the case file notes whether or not there were concurrent dependency and 

criminal cases under investigation and moving toward disposition. They would

then inform the designated gatekeeper, who would have access to the BSO files,

of the need to start tracking both dependency and criminal outcomes. Th

g

y’s Office (SAO) felt that this step should wait until the completion of the

pilot. The State Attorney’s Office, however, would work with the BSO 

gatekeeper to provide criminal outcomes when requested. This pilot would ru

for one year and include an evaluation component to monitor the process and 

analyze outcome data. The feedback loop would include the child welfare 

investigators initially and case managers once the investigative case is closed

transferred to the service provider. In Broward County, the private lead agency

ChildNet, which has been fully operational since April 2004. The Principal 

Investigator on the current study has an established relationship with ChildNe

well as BSO and SAO, making the pilot project feasible from everyone’s 

perspective. Figure 17 illustrates the anticipate

li

e manager on dependency cases. The RED lines indicate the direction of 

the initial flow of data and the BLUE lines indicate the feedback flow of data. 

Once the loop is established, it is expected that the flow through the gateke

will keep all parties informed as to the concurrent outcomes of dependency

criminal cases. 

Figure 17. Pilot: Feedback Loop between BSO and SAO 

BSO Gatekeeper

SAO Contact

ChildNet Case Manager BSO Investigator

Center for Research on Youth and Social Policy University of Pennsylvania

34

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
VI. SECONDARY ANALYSES OF CHILD WELFARE DATA 

(Florida Abuse Hotline Information System, 1996 – 2002) 

A. ANALYTIC PLAN 

The following analyses are designed to supplement findings from the 

original evaluation of the transfer of responsibility for child maltreatment 

investigations to the Sheriff’s Offices in four experimental counties. The analyse

used data from the Florida Abuse Hotline Information System (FAHIS) tha

been used in the original evaluation. Those data were supplemented by an 

additional 20 months of data to increase the number of cases in the post stage of 

the experiment. Analyses were conducted using a variety of significance

most of which compared 5 pairs of experimental and comparison counties. Tabl

11 describes the county pairs used in the analyses, as well as the number of 

months in the pre and post stages of the study for each pair. 

Table 11. County Pairs and Time Periods in Months

s

t had

tests,

e

4

 Pre Post

Manatee PAIR 1 

Lee 1 

18 56 

 

Manatee PAIR 2 

Sarasota 

18 56 

 

Pinellas PAIR 3 

Hillsborough 

34 46 

 

Pasco PAIR 4 

L 2

39 41 

ee

 

Broward 

PAIR 5 

Palm Beach 

42 32 

Please note that there was a six-month transitional stage for two of the five 

xperimental counties (Manatee and Broward); however, the reports from these 

onths were e the analytic sample

possible to determine which reports had been actually transferred to the 

heriff’s Offices and which had been investigated by DCF. Theses reports were 

ecessarily included in the longitudinal event history analyses. For those 

nalyses, the transitional reports wer ith the pre-stage reports for 

raphical representation and for repeated event statistical analyses. A second set 

pared Sheriff and Non-Sheriff counties overall. In these

instances, Pair 1 was dropped from the dataset to avoid double counting Manatee 

 

e

m ventually dropped from because it was

im

S

n

a e combined w

g

of analyses com

4

 Census (2000) data on the population in the 8 counties is provided in Appendix A. 

Center for Research on Youth and Social Policy University of Pennsylvania

35

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
and Lee. These analyses therefore involved 4 experimental and 4 comparison 

Table 12 clarifies operational definitions for outcome measures related to 

child sa ble 13 provides a schematic for the 

condary analyses, reporting the significance or impact test used, the test results, 

statistic

counties.5

fety and system performance. Ta

se

s reported, outcome measures under analysis, and the unit of analysis.

Table 12. Outcome Measures and Operational Definitions

MEASUREMENT 

VARIABLE 

For Percent Change and Effect 

Size Comparisons 

For Regre

and E

History Anal

ssion

vent 

yses 

Substan iation 

Number of reports substantiated per

county in pre, transitional, an

Prese

t d post

nce or 

absence (flag) 

periods 

Scale from 1 to 4:

1 - Abuse 

2 - Neglect

3 - Threatened Harm

Severity: Ma (indexed)

4 - Special Conditions

1, 2, and 3 as

dummy variables, 

with 4 as the 

default

ltreatment

Scale from 1 to 4:

1 - Judicial w/ Protective Svcs

2 - Judicial w/o Protective Svcs 

3 - Voluntary/Community Svcs 

Severity: Dispo e d) 

4 - D issed/Closed 

1, 2, and 3 as

dummy variables, 

with 4 as the 

default

sition (ind xe

ism

Recurrence 

# of Reports per family, victim, or 

abuser that represent a second 

repo ring the time period

Presence or 

absence (flag) 

rt du

Recidivism

# of Substantiated reports per

family, victim or abuser that

repre nd substantiated

repo ring the time period

Presence or 

absence (flag) 

sent a seco

rt du

Duration: Time to Investigative Finding 

Time between report received date N/A 

and investigative finding date 

Duration: Time to Investigative 

Closing/Open Services 

Time between report received date 

and investigation lock date, which

coincides with service plan 

implementation

N/A 

Duration: Time to Recurrence/Recidivism

N./A Time betwee

date

and substan

reports 

n

s of reports 

tiated

 

5

 emographics on caretakers, number of victims per report, and number of other children per report

in post-transfer cases provided in Appendix A. 

Center for Research on Youth and Social Policy University of Pennsylvania

36

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 13. Analytic Plan 

OUTCOME SIGNIFICANCE 

OR IMPACT 

TEST 

TEST OUTPUT STATISTICS

REPORTED 

UNIT OF

ANALYSIS

Logistic 

Regression 

Estimates the 

probability of a report 

being substantiated

Pr > ChiSq 

% Change in

Odds 

Substantiation Effect Size Estimates the 

groups 

Cohen's d Report 

Comparison magnitude of 

difference between two 

Severity: 

Maltreatment

(indexed) 

Effect Size 

parison 

E

m

differen

groups 

Com

stimates the 

agnitude of 

ce between two 

Cohen's d

Report 

Severity: Disposition 

Effect Size 

Comparison 

Estimates the Cohen's d

(indexed) 

magnitude of 

difference between two 

groups 

Report

Recurrence 

Event 

History/Survival azard or 

Hazard or 

Survival Cu

Estimated %

Change 

Estimates the 

cumulative h

survival rate

rve Family 

Recidivism

Event 

History/Survival 

Hazard or 

Survival Curve

Estimated %

ge 

y

Estimates the 

cumulative hazard or 

survival rate Famil

Chan

Ordinary Least

Squares (OLS) 

Estimates the Adj R-Sq

proportion of variance 

explained by the 

Duration: Time to variables in the model 

e Finding Effect Size 

Comparison 

rt Investigativ Estimates the 

magnitude of 

difference between two 

Cohen's d

groups 

Repo

Ordinary Least

Squares (OLS) 

Estimates the -Sq

proportion of variance 

explained by the 

Adj R

Duration: Time to variables in the model 

Investigative Closing Effect Size 

Comparison 

en's d Report Estimates the Coh

magnitude of 

difference between two 

groups 

o estimate the effect of the law en

experiment on the likelihood of reports being substantiated because the

ariable is dichotomous. Goodness-of-fit tests such as model chi-square act as 

dicators of model appropriateness and the Wald statistic tests the significance of 

Logistic regression was used t forcement

outcome 

v

in

individual independent variables. 

Center for Research on Youth and Social Policy University of Pennsylvania

37

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
As a secondary analysis, effect sizes were calculated to determine the 

pact of the transfer on substantiation, as well as the impact on maltreatment and 

disposition severity. Effect size (ES), b , is th to

statistic that indicates the difference in outcome between an a ipan

an experimental grou articipan group. U ificance

testing, ES measures ude of in on

sample size. This quality makes it a pa ethod for analyzing large 

datasets. The most commonly used statistic is Cohen’s d, calculated as the 

difference in means between the exper ontrol groups divided by the

standard deviation of either group if the variances of the two groups are 

homogenous. Zaslow er, and ) used an e of .3 or

higher as “policy-rele ir ana outcome are-to

work strategies. In commenting on th ary report to the 

Departm nt of Health and Human Serv e researchers stated that: 

th s aside are so small that, 

while they are reliable s ntinued 

monitoring over time, m int in tim ited 

impor c en tim

the threshold for policy relevance does not req impa

be "large" in magnitude eet the criterion. By setting 

the thr ay abl at we

are being inclusive in id stances of possible harm as 

well as of possible beneficial effects on children, without focusing 

on eff sm f limited importance ... We 

also id pacts for which effect sizes substantially 

eeded the threshold for policy relevance, that is, were .50 or 

r

Based on this researc t stud olicy-relevant effect

size as a measure of impact. 

Event history sed ce and recidivism. 

Event history analysis (also called surv azard analysis, and failuret ro istical techniques used with lo l data t

contain both dates and events that may appen fo in the

dataset (Allison, 1984). Event history ituations where an

event might not happen for all cases an cases are observed for differing 

eriods of time. Measures of central tendency, such as a mean, do not work well 

unless there is complete data (the full survival time) for every unit in the set. If

there is

observation point, such information would not 

be reflected in the mean length of time to recurrence or data regarding incidence 

of recurrence. This is true, also, for cases that do not complete the study period 

im

roadly speaking e name given

verage partic

a

t in

p and a p

the magnit

t in a control

an effect without be

rticularly useful m

nlike sign

g dependent

imental and c

, McGrod

vant” in the

Moore (2000

lysis of child

is decision in a summ

ices, th

effect siz

s from welf -

e

This reshold set impact findings that

tatistically and warrant co

ay at this po

hildren's developm

e have lim

t. At the same

uire that an

tance in terms of e, 

ct

in order to m

, we can be reason

entifying in

eshold in this w y confident th

ects that are so

entify those im

all as to be o

exc

large ...

h, the curren y also uses .3 as the p

analysis was u to examine recurren

ival analysis, h

ime analysis) is a g up of stat ngitudina

r all units

hat 

or may not h

analysis is useful in s

d when

p

potential that an event could occur after the observation period, or that 

cases are excluded from the study without the event occurring, event history 

analysis is preferred because it can control for censoring, that is, when an event

does not occur within the study period. For example, if a recurrence of child 

maltreatment occurs following the

Center for Research on Youth and Social Policy University of Pennsylvania

38

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
due to d

ates 

survival

fluence of

model variables on recurrence, recidivism, time to investigative finding, and time 

to investigative

recurrence and because

it is not based

underlying sur

rate (rather tha

(covariates); n

function. Cox'

Ordinary Least

transfer on the

disposition. 

B.

ily, and 2) a report-based Family History 

ropping out or other causes of attrition, such a moving outside of the 

county. 

Event history analysis produces a survival rate and a hazard rate. The 

survival rate is an individual unit’s likelihood of surviving past a particular time 

(t) without experiencing the event of interest. For example, the analysis estim

the likelihood that a particular family will not have a recurrence of child 

maltreatment by a six-month follow-up observation point. A survival curve

demonstrates the proportion of the sample that “survives” (remains without a 

recurrence of child maltreatment) as a function of time. A reverse of the

rate is the hazard rate, which indicates “the probability that an event will occur at

a particular time to a particular individual” (Allison, 1984). 

Additionally, regression was used to estimate the proportional in

closing. The Cox Proportional Hazard Model was used for 

recidivism. It is the most general of the regression models

on any assumptions concerning the nature or shape of the 

vival distribution. The model assumes that the underlying hazard 

n survival time) is a function of the independent variables 

o assumptions are made about the nature or shape of the hazard 

s regression model is considered a nonparametric method. 

Squares (OLS) regression was used to estimate the effect of the

duration of investigations and the time between report and 

ADMINISTRATIVE DATA 

The study created two longitudinal analytic datasets suitable for Event 

History analyses: 1) A report-based Family History Dataset, which includes all 

reports associated with a fam

Substantiated Report Dataset, which includes all substantiated reports associated

with a family. These analyses take into consideration issues such data censoring 

and varying durations of post-takeover stage for each of the three experimental 

counties. These datasets were transformed to accommodate all other types of 

analyses undertaken by the study.6

C. SAMPLE DESCRIPTION 

The original sample for the study consisted of all reports submitted 

through Florida’s centralized hotline to the counties involved in the study. This

sample was stratified into three experimental stages: Pre, Transitional, and Post.

 

6

 Although we anticipated having a Caretaker-Abuser Career Dataset at the same time, we 

discovered that that many of the substantiated reports lack perpetrator identification, which

mitigates against the usefulness of this dataset. Therefore, we will not submit the third dataset as

originally proposed. 

Center for Research on Youth and Social Policy University of Pennsylvania

39

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
As mentioned previously, the problem with the reports in the transitional stage

was three-fold: 1) there was no clear record of which reports were transferred to 

e Sheriff’s Offices during that stage; 2) the number of reports per county was 

very sm ed

sco’s comparison 

county (Lee 2) radically increased the number of reports, resulting in an 

imbalan

th

all relative to the number in the other stages; and 3) the stage only appli

to two of the four experimental counties. For all of these reasons, reports from

that stage were not included in the pre-post analytic comparisons except for the 

event history analyses where they were flagged if they represented either

recurrence or recidivism.

7

 

Table 14 indicates the number of reports in the final sample by county and

stage. All counties increased the number of reports they received, with the 

exception of Pinellas, Hillsborough and Pasco. However, Pa

ce in that county pair during the post period. Table 15 reports the number 

of families involved in the reports. 

Table 14. Sample Description: Number of Reports 8

 Pre Post Total 

PAIR Manatee 2835 9701 12536

1 Lee 1 3823 14837 18660 

 

PAIR Manatee 2835 9701 12536

2 Sarasota 2177 8375 10552

 

PAIR Pinellas 23046 19368 42414 

3 Hillsborough 27327 24018 51345 

 

PAIR Pasco 10104 7732 17836 

4 Lee 2 11447 19872 31319 

 

PAIR Broward 23590 30103 53693 

5 Palm Beach 18177 22368 40545 

 

TOTAL 122526 156375 278901

 

7

 Number of reports in transitional stage: Manatee=842; Lee 1=1053; Broward=4308; Palm

=3207

 Beach 

ictims and other children per report is provided in Appendix A. 8 Data on number of v

Center for Research on Youth and Social Policy University of Pennsylvania

40

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 15. Sample Description: Number of Families 9

 Pre Post TOTAL 

Manatee 2245 6304 8549 PAIR 1 Lee 1 2926 8937 11863

 

Manatee 2245 6304 8549 PAIR 2 

Sarasota 1770 5489 7259

 

Pinellas 14961 13558 28519 PAIR 3 Hillsborough 17852 16163 34015 

 

Pasco 6647 5615 12262 PAIR 4 Lee 2 7274 11206 18480 

 

Broward 17747 21445 39192 PAIR 5 Palm Beach 12503 15308 27811 

 

TOTAL 83925 104025 187950

D. RESULTS: ANALYSES CO PAIRS 

EPOR ILE R INVESTIGATION 

 As mentioned previously, the transfer of maltreatment investigations to the 

Sheriff’s Office was mot by ern ety and a belief that more 

dir la t in men t act as a deterrent. Legislators hoped 

that the transfer would result in fewer incidents of child maltreatment and better 

investigations of the incidents them s. T ple description above 

indicates here was a ase tha crease in incident reports to 

t l of the ou vol thee study. However, the

im o peri sta the number of reports per family differs 

by county pair. 

(T that the impact is only 

gnificant (d=>.3) in the county pairs that involve Manatee, possibly due to the 

nger post periods in those county pairs (56 months). The fact that the 

gnificant effects apply to both experimental and comparison counties suggests 

at the transfer alone did not account for the impact. Although Lee 2 

emonstrated a large increase in the number of reports during the post period, this 

crease did not have a significant impact. 

OF UNTY

I. R TS F D FO

ivated a conc for child saf

ect w enforcemen volve t migh

selve he sam

that t n incre rather n a de

he Hot

pact

ine in five eight c nties in ved in

f the post ex mental ge on

An effect size comparison reveals able 16)

si

lo

si

th

d

in

9

 Demographics on caretakers is provided in Appendix A. 

Center for Research on Youth and Social Policy University of Pennsylvania

41

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 16. Impact of Post Experimental Stage on Number of Reports

The significance or impact of the transfer of investigations to law 

enforcemen n om three 

erspectives: 1) Differences in the percent of reports substantiated pre and post 

Cohen's d Sig Impact

Manatee 0.28 X PAIR 1 

Lee 1 0.3 X 

 

Manatee 0.28 X PAIR 2 

Sarasota 0.3 X 

 

Pinellas -0.11 PAIR 3 

Hillsborough -0.04 

 

Pasco 0.15 PAIR 4 

Lee 2 0.15 

 

Broward 0.09 PAIR 5 

Palm Beach 0.01 

II. SUBSTANTIATION 

t o substantiation in the county pairs was explored fr

p

the transfer for Sheriff and non-Sheriff counties; 2) Odds ratio estimates of 

substantiation by county pair; and 3) Effect size comparison of the impact of the 

post period in both Sheriff and non-Sheriff counties. 

Change in Percent of Substantiated Reports by County Pair

Table 17 reflects the difference pre and post in the percentage of report

substantiated. All counties, with the exception of Palm Beach, decreased the 

percentage. Pinell

s

as and Lee1 exhibited the largest decrease; making it unlikely 

that law enforcement alone had any effect on substantiation in terms of straight 

percentage change. 

Center for Research on Youth and Social Policy University of Pennsylvania

42

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 17. Pre-Post Difference in Percent of Substantiated Reports 

Pre Post

 # 

Substantiated

% of

Total 

# 

Substantiated

% of

Total 

Change in %

Substantiated

Manatee 1790 63.14 5486 56.55 -6.59 PAIR 1 

Lee 1 1436 37.56 4049 27.29 -10.27

 

Manatee 1790 63.14 5486 56.55 -6.59 PAIR 2 Sarasota 1186 54.48 3570 42.63 -11.85

 

Pinellas 12240 53.11 9336 42.18 -10.93 PAIR 3 Hillsborough 16039 58.69 12525 52.15 -6.54 

 

Pasco 4567 45.2 3261 42.18 -3.02 PAIR 4 

Lee 2 3902 34.09 5943 29.91 -4.18 

 

Broward 12068 51.16 15118 50.22 -0.94 PAIR 5 

Palm Beach 9072 49.91 11224 50.18 0.27 

 

TOTAL 62360 50.85 70512 45.09 -5.76 

Odds Ratio Estimates by County Pairs

eriod.

impact on substantiation: 

umber of allegations, number of victim

prelimi ndicated 

at the move might affect outcomes such as substantiation; therefore a variable 

was cre

ch

ated by the interaction statistics in Table 18, the odds 

xpressed as a percentage) of a report being substantiated increased in Manatee, 

inellas and Pasco after the investigative transfer to law enforcement when 

ompared with themselves pre-transfer and with their comparison counties pre 

nd post. The exception is Broward, where the odds percentage decreased (-

0.3). This finding supports one of the assumptions behind the legislative transfer 

that the police will be more effective as investigators because they are more 

ccustomed to pursuing investigations aggressively. It may be that Broward does 

ot demonstrate the same increased odds as the other Sheriff counties because it 

ad the shortest post period in which to yield results. 

Logistic regression models were run for each county separately and the 

county pairs together to see whether the odds of a report being substantiated 

changed significantly in the experimental counties during the post transfer p

The models included demographic control variables on both victims and 

caretakers as well as the count variables most likely to

n s, and number of other children. A 

nary analysis of families that moved from one report to the next i

th

ated to indicate whether reports reflected a family move. A breakdown of

the significance of the chi-squares for each of the variables in the model for ea

county pair is provided in Appendix B. 

As demonstr

(e

P

c

a

1

–

a

n

h

Center for Research on Youth and Social Policy University of Pennsylvania

43

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 18. Odds (percentage) of Substantiation by County Pair 

 PAIR 1 PAIR 2 PAIR 3 PAIR 4 PAIR 5 

 VARIABLE Man-Lee Man-Sar Pin-Hills Pas-Lee Br-PB

Post Period -44.1 -43.9 -26.0 -41.5 -5.6 

Experimental County 192.1 44.4 -15.8 75.2 8.1

Post * Exp. Interaction 29.9 26.7 5.3 45.8 -10.3 

* c odds are significant (<.0 cept fo inellas-H ough 

inte n

 

od

including f the t on e unty, ded in ndix B

Effect Size Compa by Co air

Percent

ractio

hanges in 001) ex r the P illsbor

.

A full report on the contribution of all variables to the county pair m els,

an analysis o impac ach co is inclu Appe .

rison unty P

Th pectiv ubstan is pro by an e ize

com arison of the impact of the transfer onstrated in 

Table 1 pact of the er on s tiatio ars to b ligible.

able 19. Effect Size Impact of Transfer on Substantiation by County 

e final pers e on s tiation

 by county pair. As dem

vided ffect s

p

9, the im transf ubstan n appe e neg

T

Pair 

 Cohen's d Sig Impact

Manatee -0.12 PAIR 1

Lee 1 -0.24 

None 

 

Manatee -0.12 PAIR 2

Sarasota -0.11 

 None 

 

Pinellas -0.11 PAIR 3

Hillsborough -0.14

 None 

 

Pasco -0.06 PAIR 4

Lee 2 -0.08 

 None 

 

Broward -0.02 PAIR 5

Palm Beach 0.00 

 None 

Summary of Findings on Substantiation

The impact of the transfer on the number of reports is difficult to interp

however, because the post stage of the experiment was impacted by a change in 

the administration of the Hotline itself. The administrative change was motivated

by a series of high-profile child deaths. Consequently,

ret, 

the new administration put 

pressure on Hotline intake workers to accept reports for investigation to avoid 

Center for Research on Youth and Social Policy University of Pennsylvania

44

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
missing a potentially lethal incident. Although the number of reports in Manatee,

ee and Sarasota was impacted significantly during the post experimental stage, it 

is unlikely that the transfe stig the s Of a as

responsible for the impac

t coun creas e number of reports they investigated, 

they did not increase the percentage of reports they substantiated, with the 

e ere t rcenta rease ( was neg le. H er,

post

ge, with the exception of Pair 5 (Broward-Palm Beach). The 

Sheriff’s Offices are yielding significantly different results than 

e difference is primarily one 

f incre parison illustrates, this 

act.

L

r of inve ations to Sheriff fice in M natee w

t.

Although mos ties in ed th

xception of Pasco, wh he pe ge inc .27) ligib owev

the odds percentage of being substantiated increased in all county pairs in the

experimental sta

decrease there (-10.3) may reflect the relatively short time period of the post 

experimental stage in that county pair. Overall, the odds percentage increased 

(7.7) for the Sheriff’s Counties in the post experimental stage. These findings 

suggest that the

DCF in their ability to substantiate cases and that th

o ased odds. However, as the effect size com

significance may not be strong enough to demonstrate a policy relevant imp

III. SEVERITY 

Maltreatment Severity

As ted previou wa ectation on the part of legislators

that the transfer of respons nt investigations to the Sheriff’s 

Offices would result in stronger investigations and, possibly, increase 

substantiation rates. Th e was also a belief that more direct law enforcement 

involveme d welfar ld act terrent, possibly reducing not only

th en ltreatme severity. For purposes of analysis,

maltreatment severity w irst conceptualized as ranging on a 4-point index from

abuse (mos ) to spec ndition t severe). Special conditions

include custody issues, jurisdictional mistakes, etc., which do not indicate level of 

severity and result in dismissals or transfers. 

easured as the percentage of reports 

substantiated at the high level on the maltreatment index. Table 20 compares the 

pr ch those p ages b ty pair. All counties decreased the 

percentage of substantiated high severity reports, making it unlikely that the 

ansfer of investigations produced the decreases. As a second measure of

hanges in severity, effect sizes were calculated for the impact of the transfer on 

maltreatment index for each county 

). In this comparative analysis of the difference in impact on the county 

pairs, o

no sly, there

ibility for m

s some exp

altreatme

er

nt in chil e wou as a de

e incid ts of ma nt, but also their

as f

t severe ial co s (leas

Changes in severity were m

e-post anges in ercent y coun

tr

c

maltreatment severity, using the mean of the

(Table 21

nly Broward and Palm Beach (Pair 5) yielded policy relevant effect sizes. 

However, as the impact was the same on both experimental and comparison 

counties, it is not likely that the impact can be attributed to the transfer alone. 

Center for Research on Youth and Social Policy University of Pennsylvania

45

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 20. Pre-Post Difference in Percent of Reports Substantiated with 

High Index Maltreatment Severity 

Pre Post Number Percent Number Percent 

Change in

Percent 

Manatee 756 42.23 1874 34.16 -8.07 PAIR 1

Lee 1 603 41.99 1358 33.54 -8.45 

 

Manatee 756 42.23 1874 34.16 -8.07 PAIR 2 Sarasota 535 45.11 1244 34.85 -10.26

 

Pinellas 4873 39.81 3256 34.88 -4.93 PAIR 3 Hillsborough 5926 36.95 4366 34.86 -2.09 

 

Pasco 1838 40.25 1035 31.74 -8.51 PAIR 4 

Lee 2 1440 36.90 681 33.37 -3.53 

 

Broward 4456 36.92 4233 28.00 -8.92 PAIR 5 

Palm Beach 3269 36.03 3005 26.77 -9.26 

able 21. Effect Size Impact of Transfer on Maltreatment Severity by 

County

T

 Pair

 Cohen's d Policy Relevant 

Impact

Manatee 0.19 PAIR 1 

Lee 1 0.24 

 

 

 

Manatee 0.19 PAIR 2 

Sarasota 0.21 

 

 

 

Pinellas 0.12 PAIR 3 Hillsborough 0.09

 

 

 

Pasco 0.09 PAIR 4 

Lee 2 -0.1 

 

 

 

Broward 0.37 X PAIR 5 Palm Beach 0.30 X 

Center for Research on Youth and Social Policy University of Pennsylvania

46

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Disposition Severity

Although there was less expectation that the transfer of investigations 

would impa on court dispositions ositions can be view

investigative work in the s effe estig ovide the court w

b r ith whic make a ition de

many other variables are like influen osition rt from ality of

investigations, the study only ducted a ct size

th in een cou .

Disposition severity was conceptual as rang n a 4-p dex

f c s w urt supe n to cas missed sed aft

assessment. Severity was first m asured atment severity, as a 

percentage of substantiated reports result a high l

in b onstrates that the counties increased the percent of reports 

yield isposition, with the exception of ard, Pa ach, and

Lee 2. Lee County, in both Pair 1 and P exhibit cularly

increases. 

ond measure, the comparative effect size analysis (Table 23)

ty

relevant level. Because the significance was 

plit between experimental and comparison counties over three county pairs, it is 

impossible to ribute the chan position sev stigative

transfer alone. 

Table 22. of Reports Substantiated with 

dex Dispositi verity

ct , disp ed as one outcome of 

ense that ctive inv ations pr ith

etter info mation w h to dispos termination. Because so 

ly to ce disp s apa the qu

con

nties

n effe analysis on differences in 

e mean dex betw

ized ing o oint in

rom judi ial disposition ith co

e

rvisio

si

es dis

a e

or clo er

milarly to m ltr

ing in evel on the disposition 

dex. Ta le 22 dem

ing a high level d Brow lm Be

air 4, s parti large

As a sec

demonstrated that both Lee County in both Pair 1 and Pair 2, and Broward Coun

in Pair 5, were impacted at a policy

s

att ges in dis erity to the inve

Pre-Post Difference in Percent 

High In on Se

Pre Post Number Percent Number Percent 

Change in

Percent 

Manatee 212 11.84 712 12.98 1.14 PAIR 1 

Lee 1 132 9.19 1039 25.66 16.47 

 

Manatee 212 11.84 712 12.98 1.14 PAIR 2 Sarasota 133 11.21 635 17.79 6.58 

 

Pinellas 1555 12.70 1765 18.91 6.21 PAIR 3 Hillsborough 2467 15.38 2409 19.23 3.85 

 

Pasco 576 12.61 344 10.55 -2.06 PAIR 4 Lee 2 565 14.48 656 32.14 17.66 

 

Broward 2091 17.33 1510 9.99 -7.34 PAIR 5 Palm Beach 1053 11.61 1040 9.27 -2.34 

Center for Research on Youth and Social Policy University of Pennsylvania

47

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 23. Effect Size Impact on Disposition Severity by County Pair 

 Cohen's d Policy Relevant 

Impact

Manatee -0.05 

PAIR 1

Lee 1 0.30 X 

 

Manatee -0.05 

PAIR 2

Sarasota 0.06 

 

Pinellas -0.17 

PAIR 3

Hillsborough -0.07 

 

Pasco -0.10 

PAIR 4

Lee 2 0.30 X 

 

Broward 0.30 X 

PAIR 5

Palm Beach -0.25 

Summary of Findings on Severity

In brief, there did not seem to be any real impact of the transfer of 

investigations on either the severity of maltreatment or the severity of disposition 

s changes in these measures affected the experimental and comparison counties 

IV. DURAT

On e identified erns of c welfare sts and ates is 

the length time children are involved in the system be re attaining

p c ata availa or the c study d t allow es on

perm es; however, it was p e to det e pre-p ects on

the l gth etween o g a case for investigation and rendering a 

finding for the investigation. It was also p e to de e pre-p ects on

the time between opening and closing a case for investig n. As the case 

cl oi with opening a case for es, the is is im nt in

te m n treatment hildren milies. he two n

analyses, the length of investigation is more closely linked to a possible impact of 

transferring investigative responsibility to nforce The se -- the

tim a servi n -- is a ed by th

apacity of services providers, the willingness of their part to accept cases for 

service, and complexity of family needs addressed through service planning. The 

a

equally. 

ION 

e of th conc hild analy advoc

of fo

ermanen y. The d ble f urrent id no analys

anency outcom

en

ossibl ermin ost eff

of time b penin

ossibl termin

io

ost eff

at

osing c

rms of i

ncides servic analys porta

pact o for c and fa Of t duratio

law e ment. cond

e between opening a case and implementing ce pla ffect e

c

Center for Research on Youth and Social Policy University of Pennsylvania

48

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
study also measured the change in time between investigative finding and case 

closing/service opening. 

ion

f mean # of days; and effect size comparison of impact. A preliminary 

frequency distribution of duration

on the same day the report was receive

closed and services opened the same report as recei d in 2.2% of the

cases; and fin ere rendered the e day the case was closed in 17.46% of 

the cases. 

Ordin st Squar s: Es es for Duration ariables

Duration variables were analyzed using regression; frequency distribut

o

variables revealed that findings were rendered 

d for 3.4% of the cases; the case was 

day a w ve

dings w sam

ary Lea e timat V

OLS regression models were run on both duration variables, using the 

same variables as the logistic regression model for substantiation, with the 

adju -Sq ted for county pa able 24). The estimates reveal that its 

respective model explained a very small proportion of the variance in either 

variable. 

able 24. OLS Estimates for Time to Investigative Finding and Time to 

Case Closing/Services Open 

sted R repor irs (T

T

Adj R-Sq

 

Time to 

Finding 

Time to 

Closing 

Manatee PAIR 1 

Lee 1 0.110 0.013 

 

Manatee PAIR 2 Sarasota 

0.068 0.029 

 

Pinellas PAIR 3 0.076 0.027 Hillsborough

 

Pasco PAIR 4 Lee 2 0.207 0.037 

 

Broward PAIR 5 Palm Beach 0.040 0.038 

Time to Investigative Finding

The length of time it takes for an investigator to render a finding on a 

reported incident of maltreatment varies, of course, by the complexity of the 

particular allegation or set of allegations. In cases where there is an abundance of 

clear evidence the finding may be rendered on the same day the report is filed. In

Center for Research on Youth and Social Policy University of Pennsylvania

49

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
other cases, it may require multiple visits and/or multi-disciplinary consultations

One of the assumptions ma

.

de by the legislature when the transfer to of 

vestigative responsibility to the Sheriff’s Offices was implemented was that law 

ed and finding rendered by county pair. The length of time increased 

r all counties, with the largest increase in Pasco and the smallest in 

illsborough. Comparing experimental and comparison counties, the larger 

creas

xperimental counties. 

#

in

enforcement would be more efficient in gathering evidence, weighing its 

significance, and decided on a finding. This study measured the time to 

investigative findings as a mean number of days from report received to finding 

documented. 

 Table 25 reports the pre-post difference in mean number of days between 

report receiv

fo

H

in es in time to investigative findings occurred in four of the five 

e

Table 25. Pre-Post Change in Time to Investigative Finding (mean

days) 

Pre Post Difference County Diff

Manatee 48.40 73.80 25.40 PAIR 1 

Lee 1 15.43 46.18 30.75 5.35 

 

Manatee 48.40 73.80 25.40 8.70 PAIR 2 Sarasota 49.45 66.15 16.70 

 

Pinellas 55.48 93.24 37.76 31.76 PAIR 3 Hillsborough 51.51 57.51 6.00 

 

Pasco 63.33 149.26 85.93 51.84 PAIR 4 Lee 2 24.45 58.54 34.09 

 

Broward 61.91 96.28 35.07 26.25 PAIR 5 Palm Beach 65.87 74.69 8.82 

Table 26 reports the actual impact of these increases in each county. All 

e ntal counties were significantly impacted in terms of increased length of 

ti e ort received ding rendered. The greatest impact in the 

experimental counties was in Pasco. Of the comparison counties, only Lee was 

s t ted and thi ct revealed itself in both county pairs in 

w e .

xperime

me betw en rep and fin

ignifican

hich Le

ly impac s impa

participates

Center for Research on Youth and Social Policy University of Pennsylvania

50

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 26. Effect Size Impact on Time to Investigative Finding by County 

Pair 

 Cohen's d Policy Relevant 

Impact

Manatee 0.30 X 

PAIR 1

Lee 1 0.64 X 

 

Manatee 0.30 X 

PAIR 2

Sarasota 0.25 

 

Pinellas 0.43 X 

PAIR 3

Hillsborough 0.10

 

Pasco 0.69 X 

PAIR 4

Lee 2 0.75 X 

 

Broward 0.34 X 

PAIR 5

Palm Beach 0.11 

Time to Case Closing

o ild welfare had been plagued with a huge backlog of 

open cases prior to the beginning of the law enforcement experiment; this backlog 

m decision to transfer in ations to the 

Sheriff’s Offices. There was a need for the inv n prove

performance in the area of timely case closings and an expectation that the 

Sheriff’s Offices would be more efficient in clearing up the ba As th

investigative closing date corresponds to the service plan opening date, decreases 

in time to closing are desirable in t s of moving children and families into 

tr a possible a maltreat ncident.

7 reports the pre-post difference in mean number of days between 

Fl rida’s ch system

ay have played a part in the legislative vestig

estigating age cies to im

cklog. e

erm

eatment s soon as fter the ment i

Table 2

report received and investigation closed/services opened. Again, all counties 

increased the length of time to investigative closing, with four of the five 

experimental counties experiencing larger increases than their comparison 

counties. The largest increase was again in Pasco, with the smallest increase in 

Hillsborough. 

Center for Research on Youth and Social Policy University of Pennsylvania

51

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 27. re-Post Change in Time to Case Closing/Services Open (mean # 

days)

P

 Pre Post Change County Diff

Manatee 57.66 82.39 24.73 7.39 PAIR 1 

Lee 1 28.69 60.81 32.12 

 

Manatee 57.66 82.39 24.73 6.56 PAIR 2 

Sarasota 67.50 85.67 18.17 

 

Pinellas 74.11 115.60 41.49 36.25 PAIR 3 Hillsborough 59.57 64.81 5.24 

 

Pasco 92.37 193.95 101.58 72.31 PAIR 4 

Lee 2 40.64 69.91 29.27 

 

Broward 95.31 108.15 12.84 11.66 PAIR 5 Palm Beach 90.19 91.37 1.18 

8 compares the impact of the transfer county by county on the 

he exception of Broward County, the transfer 

pacted all experimental counties significantly; the only comparison county 

by

Table 2

length of investigations. With t

im

significantly impacted was again Lee in relationship to both Manatee and Pasco.

The largest impacts were in Pasco and Lee counties. 

Table 28. Effect Size Impact on Time to Case Closing/Services Open

County Pair 

 Cohen's d Policy Relevant 

Impact

Manatee 0.28 X PAIR 1 Lee 1 0.58 X 

 

Manatee 0.28 X PAIR 2 

Sarasota 0.24 

 

Pinellas 0.42 X PAIR 3 Hillsborough 0.08

 

Pasco 0.78 X PAIR 4 

Lee 2 0.55 X 

 

Broward 0.12 PAIR 5 Palm Beach 0.11 

 

 

Center for Research on Youth and Social Policy University of Pennsylvania

52

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Summary of Findings on Duration

t ime to duration, the desired decreases in d n were o

fo ing in the time between investigative findings and case closing/services 

open. As these decreases were split between experimental and comparison 

counties, it is unlikely they can be attributed impact of the investigativ

transfer. 

as s to have effected m atively th of the o

counties. I to de an exact reason for such disproportionately 

large increases in duration, although findings from the previous study indicate that 

P s st resistant of the Sheriff’s Offices to the change. In fact, Pasco 

delayed accepting the transfer for 6 months after the mandated start date due to 

contract negotiation disputes that were difficult to a

l e ases in duration times are due to this re ce, whic

ave contin hey fin ccepted the transfer and began investigations. 

on

. Despite this setback, Lee 

as able to decrease the time between rendering an investigative finding and 

losing the case to open it for service.

RECURRENCE AND RECIDIVISM 

Pos ly the mos t indic afety is a decrease in

recurrence and/or recidivism defined in this report, recurrence is the presence 

o a port of m atment per fa

Recidivism s the presen ore than one substantiated report of maltreatment 

per fam

Frequency of Recurrence and Recidivism: Percentage Change

In

rthcom

erms of t uratio nly

to the e

P co seem been ore neg an any ther

t is difficult termine

asco wa the mo

 resolve. It is possible th t a

east som of the incre h may

ued after t

sistan

h ally a

Of the comparison counties, Lee experienced the most negative effects

time to finding and closing. Again, findings from the previous study may shed

light on the situation. That study discovered that Lee County had suffered a 

serious cutback in its service funding prior to the investigative transfer. The 

increases in duration may reflect the county’s diminished capacity to provide 

services and have little to do with investigative change

w

c

IV. 

sib t importan ator of child s

. As

f more th n one re altre mily by county and pre-post stage. 

i ce of m

ily by county and pre-post stage. 

ecurrence and recidivism is through a 

comparative frequency distribution. Table 29 ports on the percentage changes

pre and post in the recurrence per family. Although Manatee in both Pair 1 and 

Pair 2 experienced a large increase in the percentage of reports that represent a 

recurrence in the post stage, the comparison co ties in those pairs also 

experienced large increases. The size of the increase in Manatee, Lee and 

d to th t that the post stage in these counties was much 

A broad way to look at changes in r

re

un

Sarasota may be relate e fac

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
longer than in any of the other county pairs. This extended post stage gives 

milies more time in which to recur, so that comparisons among counties and 

the differential length of their post stages. 

the other three county pairs, Lee 2 experienced the largest increase in the 

ercent

e

fa

county pairs must be viewed in light of

In

p age of families with recurrence. 

Table 29: Pre-Post Change in Percentage in Families with 

Recurrenc

Pre Post # Recurrence % of Total # Recurrence % of Total

Change in %

Recurrence

Manatee 590 20.81 3397 35.02 14.21 PAIR 1 Lee 1 897 23.46 5900 39.77 16.31 

 

PAIR 2 Manatee 590 20.81 3397 35.02 14.21 

 Sarasota 407 18.70 2886 34.46 15.76 

 

PAIR 3 Pinellas 8085 35.08 5811 30.00 -5.08 

 Hillsborough 9475 34.67 7855 32.70 -1.97 

 

PAIR 4 Pasco 3457 34.21 2117 27.38 -6.83 

 Lee 2 4173 36.45 8666 43.61 7.16 

 

PAIR 5 Broward 5843 24.77 8658 28.76 3.99

 Palm Beach 5674 31.22 7060 31.56 0.34

 

TOTAL 38601 31.50 52350 33.48 1.98 

recurre

investig

screening procedures came under intense scrutiny, causing them to feel pressured 

into tak

Table 30 demonstrates that the pattern for family recidivism is the same as 

for recurrence, although increases and decreases are much smaller. Comparing 

changes in percentages between recurrence and recidivism (Figure 18), it 

becomes clear that with the exception of Pasco and Hillsborough families 

recidivated much less than they recurred. As discussed previously, the increase in 

nce may be due to a change in the Hotline administration prior to the 

ative transfer to the Sheriff’s Offices. Hotline counselors and their 

ing in more reports. A separate Hotline evaluation found that counselors 

began sending almost 90% of all calls out for investigation.10 The difference 

between percent recurring and percent recidivating suggests that there may have

been many spurious reports send to all counties

 

10 Gelles, R., Cohen, B., Wilson-Spigner, C., Kinnevy, S. and Huang, V. (2000). Evaluation of the 

Florida Child Abuse Hotline. Report to the Florida Dept. of Children and Families, Tallahassed,

FL 

Center for Research on Youth and Social Policy University of Pennsylvania

54

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Table 30. Pre-Post Percentage Change in Families with Recidivism 

Pre Post # Recidivism % of Total # Recidivism % of Total

Change in %

Recidivism 

Manatee 368 12.98 1835 18.92 5.94 PAIR 1 

Lee 1 360 9.42 1593 10.74 1.32 

 

PAIR 2 Manatee 368 12.98 1835 18.92 5.94 

 Sarasota 266 12.22 1313 15.68 3.46

 

PAIR 3 Pinellas 4382 19.01 2667 13.77 -5.24

 Hillsborough 5739 21.00 3947 16.43 -4.57

 

PAIR 4 Pasco 1621 16.04 816 10.55 -5.49

 Lee 2 1468 12.82 2550 12.83 0.01

 

PAIR 5 Broward 3206 13.59 3979 13.22 -0.37

 Palm Beach 2925 16.00 3260 14.57 -1.43

 

TOTAL 20335 16.60 21960 14.04 -2.56

F parison Percentage Changes in Recurrence and

Recid

igure 18. Com between 

ivism

-8.3

-15.0

-8.3

-12.3

-4.4

-1.8

-0.2 -7.2

ManSara

Hillsborough

Palm Bea

2.6

1.3

Manatee

atee

sota

Pinellas

Pasco

Lee 2

Broward

ch

Lee 1

E. SUMMARY OF FINDINGS ON COUNTY PAIR ANALYS

Overall, analyses of county pairs suggest

ES

that the impact of law 

enforcement experiment is negligible, with significant effects often applicable to 

both experimental and comparison counties, suggesting that the transfer alone did 

not account for the impact. Because the post stage of the experiment was 

Center for Research on Youth and Social Policy University of Pennsylvania

55

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
impacted by a change in the administration of the Hotline itself, the differential 

increases in number of reports in some counties is difficult to interpret, although 

The

crease in the number of reports was not matched by an increase in substantiated 

reports. However, the odds percentage of a report being su iated incre

in four of th five county

p erall he She ountie e post imenta

stage. Although the odds of substantiation have seem increas to the

periment, the effect size comparison demonstrates a small impact as a result of 

th

W regard to c nges in mal ition verity, th

e n to have lit pact on either. With regard to duration of 

inve gat h of ti servic S estim establis neithe

ponsibl or m than

models. Desirable decreases in duration xperien by both iment

p countie wi indi t t e d ses w r cte by

i lf. P

th s, but t y be a able to ance to perim

elf n t sc and ding cutbacks on services in Lee. 

The findings on recurrence and recidivism are inconclusive as well. The 

me change in Hotline administration that impacted on the number of reports 

y h

xt section of the report. 

 

there does not seem to be a pattern of increase in the experimental counties.

in

bstant ased

e pairs in the post experimental stage, with the odds

ercentage increasing ov for t riff’s C s in th exper l

ingly ed due

ex

e odds change.

ith ha treatment and dispos se e

xperime t seems tle im

sti ion and lengt me to es, OL ates h that r

variable was res e f ore a small percentage of variance in their 

were e ced exper al

and com

th

arison s,

asco and Lee seem

th no ca ion tha th ecrea e e effe d

e exper

an he o

ment itse ed to experience more negative effects 

t

o

ther countie

part of Pa

his ma

fun

ttribut resist the ex ent 

its he o

sa

received ma ave impacted on recurrence increases as well. The fact that 

families tended to recur more than recidivate support this suggestion. Recurrence 

and recidivism will be further explored in the ne

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
VII. EVENT HISTORY ANALYSIS OF CHILD WELFARE DATA (1996-

2002) 

 

A more rigorous way to look at the effect of the investigative transfer on 

recurrence and recidivism is through event history analyses. These analyses

presented graphically, and summarized statistically, in three ways

are

east one report subsequent to their first report (recurrence) or at 

least one substantiated report subsequent to their first 

,

11

: 

1) As an assessment of the pre-post risk of a family experiencing at

l

substantiated report (recidivism) in either the pre or post stage

by county pairs. The results are expressed graphically by 

plotting the hazard rate against the duration between events, 

with summary statistics and tests for the hazard function. 

2) As an assessment of the pre-post chance of a family not

experiencing (surviving) recurring reports after their first report 

or substantiated reports after their first substantiated report 

(recidivism) in either the pre or post stage, by county pairs. The 

results are expressed graphically by plotting the survival rate 

.

vival,

expressed statistically as the median lifetime, which estimates 

the point in time by which half the families will have 

experienced recurrence, recidivism, or substantiated abuse. 

A. HAZARD FUNCTION ANALYSES 

The hazard function is defined as the conditional probability that an 

individual, or family, will experience an event in a given time period. The hazard 

function model in this report is designed to present an overview of trends in 

recurrence and recidivism among the families in the sample. It treats recurrence 

and recidivism dichotomously in that it looks at whether a family recurred or 

recidivated at least once after first entering the system in either the pre or post 

stage. The model also treats the event (report or substantiated report) as the only 

event impacting the hazard rate, without reference to any other co-variants. 

 

against the duration between events while controlling for 

explanatory variables. Proportional hazard modeling (Cox 

regression) was used and summary statistics are presented

3) As an assessment of the central tendency for family sur

11 Operational definitions and interpretive possibilities were derived from Singer, J.D. and Willet, 

J.B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. 

Oxford Univeristy Press: New York, NY. 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
In the hazard function model each family is followed for a duration of 18 

stage rs in the pre stage because some families actually do not 

ate within 18 months. In other words, if the family’s first report is 

post stage to

llow for recurrence. 

Table 31

recurring report d at

experienced at le

18-month duratio

Table 31. Number of Families w

Su onth

Du

months, necessarily incurring a right-censoring situation for reports in the post 

. Censoring occu

recur or recidiv

in the pre stage and they do not do recur or recidivate within 18 months, they are

defined as censored for model estimates. Censoring in the post stage occurs for 

the same reason, but also occurs when first reports happen too late in

a

reports on the number of families that experienced at least one 

uring pre-post stages by county pair, as well as those th

ast one substantiated recurring report during those stages, for an 

n.

ith Reports for Recurrence and 

bstantiated Recurrence Hazard Function Model: 18 m

ration12

COUNTY 

PAIR COUNTY Recurred Recidivated 

705 2515

Manatee 3888 513 

890 421 

PAIR 1 Lee 1 6031 2013

705 2515

Manatee 3888 513 

493 312 

PAIR 2 Sarasota 3445 1824

4263 2957

Pinellas 10002 5598

4993 3672

PAIR 3 Hillsborough 12250 7345

1854 1121

Pasco 4361 2123

2094 1034

PAIR 4 Lee 2 4853 1365

3969 2546

Broward 16579 9442

3368 2225

PAIR 5 Palm Beach 12147 7016

The hazard functions are estimated for four groups using two strata, 

county and stage, each applied to two events: new reports (recurrence) and new 

substantiated reports (recidivism). The question remains: Does the hazard rate 

 

12 Data on censoring provided in Appendix C for both 18 and 14 months duration. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
differ b

ries presents the cumulative hazard with the hazard 

functions smoothed out over time to indicate the steadiness with which the rate 

increas

,

Increases and decreases in the raw hazard rate may be unavoidable for 

ide

element of pre

teady rate, the n reinforce and sustain current practices. On the other 

and, if the hazard increases over time at a steady rate, the system needs to adapt 

or pra the rate

the s to kn r to sus e 

for the law enforcem ent w

recidivism at a stea

cilitate retatio e hazard , their underlying 

statistics are presented. For both rec , the interaction of

county and stage is ignifican s the comb ion of stages for each

county individually. The differences between county pairs lie in the contribution 

of each county to each stage; these differences allow us to determine whether the 

experimental counties are exhibiting hazard rates that are different significantly 

than their comparis ies in te the direct the hazard change

(increase o decrease) o that change (steady or variable). 

etween experimental and comparison counties before and after the transfer

of investigative responsibility to the Sheriff’s Offices. 

The hazard function graphs presented on the following pages illustrate the 

pre-post hazard rates for recurrence and recidivism for each county pair in two 

ways. The first graph in each series presents the fluctuations of the hazard over 

time and illustrates more clearly the direction of changes pre and post. The 

second graph in each se

es or decreases. The second graph is actually more valuable in assessing 

the hazard because it demonstrates more clearly whether the rate is constant

increasing or decreasing over time. 

reasons outs the control of the investigators. Achieving a steady rate of 

change, on the other hand, can be seen as stabilizing the system and adding an

dictability to future events. If hazard decreases over time at a 

s system ca

h

modify its

ystem

ctices. If

ow whethe

is unsteady in either direction, it is difficult for 

tain or modify. Of course, the desired outcom

ent experim

dy rate.

ould be a decrease in both recurrence and 

To fa the interp n of th graphs

u

t, as i

rrence and recidivism

always s inat

on count rms of ion of

r r rate of 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 1: Manatee-Lee (Graphs on pp 59 -60)

dier 

d function, clarifying 

the contributions of both county and stage to the model. The recurrence statistics 

demons

ge.

e.

The hazard for recurrence in County Pair 1 appears to decrease slightly 

after 100 or 200 days for both experimental and comparison counties during the

pre stage. The hazard for recurrence remains constant in the post stage. The 

difference in the recidivism hazard is that the decrease in the pre stage is stea

and the counties converge by the end of the stage. During the post stage, the

hazard remains constant as it did for recurrence, although the counties seem to 

move closer to convergence. 

Table 32 reports the statistics that support the hazar

trate that the significance of county is not apparent in the pre stage, 

although the contribution of Manatee approaches significance in the post sta

The recidivism statistics demonstrate that county is not significant in either stag

Table 32. Hazard Function Statistics for County Pair 1: Manatee-Lee 

Log-Rank Test of Equality over Strata Event 

Tested Strata Chi-Square DF Pr >Chi-Square Sig 

RECURRENCE Manatee-Lee 

 County and Pre-Post 655.8258 3 <.0001 X 

 County for Pre 0.8388 1 0.3597 

 County for Post 3.9922 1 0.0457 X 

 Pre-Post for Manatee 237.7218 1 <.0001 X 

 Pre-Post for Lee 413.1431 1 <.0001 X 

RECIDIVISM Manatee-Lee 

 County and Pre-Post 255.0666 3 <.0001 X 

 County for Pre 0.0961 1 0.7566 

 County for Post 0.9276 1 0.3355 

 Pre-Post for Manatee 136.4934 1 <.0001 X 

 Pre-Post for Lee 118.2129 1 <.0001 X 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Manatee-Lee Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.0000

0.0005

0.0010

0.0015

0.0020

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=LEE STAGE=Post COUNTY=LEE STAGE=Pre

COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

Manatee-Lee Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.0

0.2

0.4

0.6

0.8

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=LEE STAGE=Post COUNTY=LEE STAGE=Pre

COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Manatee-Lee Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.0000

0.0005

0.0010

0.0015

0.0020

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=LEE STAGE=Post COUNTY=LEE STAGE=Pre

COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

Manatee-Lee Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.0

0.2

0.4

0.6

0.8

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=LEE STAGE=Post COUNTY=LEE STAGE=Pre

COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 2: Manatee-Sarasota (Graphs on pp 62-63)

The hazard for recurrence in County Pair 2 also decreases after 200 days 

during the pre stage and remains constant during the post stage, where the two 

counties converge for most of the duration of that stage. The recidivism hazard 

mirrors the recurrence hazard in the pre stage, where the county influence is not 

significant. In the post stage, however, the recidivism hazard rate in Sarasota 

begins to increase, unlike the constant rate in Manatee; the county influence 

becomes statistically significant (Table 33). This finding may indicate that 

although the transfer of investigations in Manatee had no discernable effect on 

recurrence, it may have had a positive influence on the steadiness of the hazard 

rate. 

Table 33. Hazard Function Statistics for County Pair 2: ManateeSarasota 

Log-Rank Test of Equality over Strata Event 

Tested Strata Chi-Square DF Pr >Chi-Square Sig 

RECURRENCE Manatee-Sarasota 

 County and Pre-Post 515.1518 3 <.0001 X 

 County for Pre 6.2695 1 0.0123 X 

 County for Post 0.0799 1 0.7774 

 Pre-Post for Manatee 237.7218 1 <.0001 X 

 Pre-Post for Sarasota 278.056 1 <.0001 X 

RECIDIVISM Manatee-Sarasota 

 County and Pre-Post 322.5618 3 <.0001 X 

 County for Pre 1.7143 1 0.1904 

 County for Post 17.0102 1 <.0001 X 

 Pre-Post for Manatee 136.4934 1 <.0001 X 

 Pre-Post for Sarasota 173.7871 1 <.0001 X 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Manatee-Sarasota Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

0.0000

0.0005

0.0010

Hazard Function 0.0015

0.0020

DUR18

0 100 200 300 400 500 600

STRATA: ATEE STAG UNTY=M AGE=Pre

OTA S UNTY=SA TAGE=Pre

COUNTY=MAN E=Post CO ANATEE ST

COUNTY=SARAS TAGE=Post CO RASOTA S

Manatee-Sarasota Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.0

0.2

0.4

0.6

0.8

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

COUNTY=SARASOTA STAGE=Post COUNTY=SARASOTA STAGE=Pre

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Manatee-Sarasota Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.0000

0.0005

0.0010

0.0015

0.0020

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

COUNTY=SARASOTA STAGE=Post COUNTY=SARASOTA STAGE=Pre

Manatee-Sarasota Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.0

0.2

0.4

0.6

0.8

1.0

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=MANATEE STAGE=Post COUNTY=MANATEE STAGE=Pre

COUNTY=SARASOTA STAGE=Post COUNTY=SARASOTA STAGE=Pre

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 3: Pinellas-Hillsborough (Graphs on pp 65-66)

The hazard rates for both recurrence and recidivism appear to be different 

in County Pair 3 than in the Manatee county pairs. For one thing, the rates for 

both look very similar, in that slight decreases in hazard during the pre stage and 

increases in hazard in the post stage seem to be almost the same in both counties. 

The statistics indicate that the county is a significant influence on recurrence only 

in the post stage and has no significant influence on recidivism for either stage 

(Table 34). Hazard rates between the two counties vary noticeably after day 400. 

Table 34. Hazard Function Statistics for County Pair 3: PinellasHillsborough

Log-Rank Test of Equality over Strata Event 

Tested Strata Chi-Square DF Pr >Chi-Square Sig 

RECURRENCE Pinellas-Hillsborough 

 County and Pre-Post 8787.4703 3 <.0001 X 

 County for Pre 1.6782 1 0.1952 

 County for Post 10.9787 1 0.0009 X 

 Pre-Post for Pinellas 3704.0701 1 <.0001 X 

 Pre-Post for Hillsboroough 5076.4358 1 <.0001 X 

RECIDIVISM Pinellas-Hillsborough 

 County and Pre-Post 4686.9793 3 <.0001 X 

 County for Pre 3.6503 1 0.0561 

 County for Post 2.4085 1 0.1207 

 Pre-Post for Pinellas 1877.458 1 <.0001 X 

 Pre-Post for Hillsboroough 2809.2096 1 <.0001 X 

Center for Research on Youth and Social Policy University of Pennsylvania

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Pinellas-Hillsborough Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.0000

0.0005

0.0015

0.0010

0.0020

0.0025

0.0030

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY ost Y=H BOROUGH re

C Y=P LAS STAG

=HILLSBOROUGH STAGE=P

=PINELLAS STAGE=Post

COUNT ILLS STAGE=P

OUNTY COUNT INEL E=Pre

Pinellas-Hillsborough Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=HILLSBOROUGH STAGE=Post COUNTY=HILLSBOROUGH STAGE=Pre

COUNTY=PINELLAS STAGE=Post COUNTY=PINELLAS STAGE=Pre

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Pinellas-Hillsborough Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=HILLSBOROUGH STAGE=Post COUNTY=HILLSBOROUGH STAGE=Pre

COUNTY=PINELLAS STAGE=Post COUNTY=PINELLAS STAGE=Pre

Pinellas-Hillsborough Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=HILLSBOROUGH STAGE=Post COUNTY=HILLSBOROUGH STAGE=Pre

COUNTY=PINELLAS STAGE=Post COUNTY=PINELLAS STAGE=Pre

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 4: Pasco-Lee 2 (Graphs on pp 68-69)

The hazard for both recurrence and recidivism in County Pair 4 decreases 

during the pre stage, but increases during the post stage. This more radical 

change between pre and post is the same for both counties, supported by the 

statistics that indicate no significance influence by county on the model in either 

stage for either recurrence or recidivism (Table 35). This analysis seems to 

indicate that changes in hazard are not connected with the transfer of 

investigations to law enforcement. 

Table 35. Hazard Function Statistics for County Pair 4: Pasco-Lee 2 

Log-Rank Test of Equality over Strata Event 

Tested Strata Chi-Square DF Pr >Chi-Square Sig 

RECURRENCE Pasco-Lee 2 

 County and Pre-Post 1466.4145 3 <.0001 X 

 County for Pre 0.6277 1 0.4282 

 County for Post 1.4627 1 0.2265 

 868.6581 1 <.0001 X 

 587.0674 1 <.0001 X 

RECIDIVISM Pasco-Lee 2 

 County and Pre-Post 1466.4145 3 <.0001 X 

 County for Pre 0.6277 1 0.4282 

 County for Post 1.4627 1 0.2265 

 Pre-Post for Pasco 868.6581 1 <.0001 X 

 Pre-Post for Lee 2 587.0674 1 <.0001 X 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Pasco-Lee2 Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.000

0.001

0.002

0.003

0.004

0 100 200 300 400 500 600

DUR18

STRAT ee2 STAG CO TY=Lee2 e

COUNTY=PASCO ST CO TY=PAS =Pre

A: COUNTY=L E=Post

AGE=Post

UN

UN

 STAGE=Pr

CO STAGE

Pasco-Lee2 Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

1.50

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=Lee2 STAGE=Post COUNTY=Lee2 STAGE=Pre

COUNTY=PASCO STAGE=Post COUNTY=PASCO STAGE=Pre

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Pasco_Lee2 Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.000

0.001

0.002

0.003

0.004

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=Lee2 STAGE=Post COUNTY=Lee2 STAGE=Pre

COUNTY=PASCO STAGE=Post COUNTY=PASCO STAGE=Pre

Pasco_Lee2 Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

1.50

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=Lee2 STAGE=Post COUNTY=Lee2 STAGE=Pre

COUNTY=PASCO STAGE=Post COUNTY=PASCO STAGE=Pre

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71

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 5: Broward-Palm Beach (Graphs on pp 71-72)

In County Pair 5, recurrence and recidivism hazard rates decrease slightly 

during the pre stage and increase during the post stage. Table 36 supports the 

significance of both county and stage separately, as well as interactively. As with 

Pasco-Lee 2, this finding indicates that changes in hazard are not specifically 

attributable to the investigative transfer. 

Table 36. Hazard Function Statistics for County Pair 5: Broward-Palm 

Beach 

Log-Rank Test of Equality over Strata Event 

Tested Strata Chi-Square DF Pr >Chi-Square Sig 

RECURRENCE Broward-Palm Beach 

 County and Pre-Post 12537.7888 3 <.0001 X 

 County for Pre 90.8911 1 <.0001 X 

 County for Post 24.3943 1 <.0001 X 

 Pre-Post for Broward 7745.163 1 <.0001 X 

 Pre-Post for Palm Beach 4740.7747 1 <.0001 X 

RECIDIVISM Broward-Palm Beach 

 County and Pre-Post 6285.9179 3 <.0001 X 

 County for Pre 90.2683 1 <.0001 X 

 County for Post 6.0929 1 0.0136 X 

 Pre-Post for Broward 4079.0895 1 <.0001 X 

 Pre-Post for Palm Beach 2181.4199 1 <.0001 X 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Broward-Palm Beach Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

H

0.000

0.003

azard Function 0.001

0.002

0.004

DU

0 100 200 300 400 500 600

R18

STRATA: C =Post TY OWARD S

CO GE=Post TY LM BEACH re

OUNTY=BROWARD STAGE

UNTY

COUN =BR TAGE=Pre

=PALM BEACH STA COUN =PA STAGE=P

Broward-Palm Beach Recurrence Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=BROWARD STAGE=Post COUNTY=BROWARD STAGE=Pre

COUNTY=PALM BEACH STAGE=Post COUNTY=PALM BEACH STAGE=Pre

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Broward-Palm Beach Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Hazard Function 0.000

0.001

0.002

0.003

0.004

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=BROWARD STAGE=Post COUNTY=BROWARD STAGE=Pre

COUNTY=PALM BEACH STAGE=Post COUNTY=PALM BEACH STAGE=Pre

Broward-Palm Beach Recidivism Hazard

County and Stage Comparison: 18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=BROWARD STAGE=Post COUNTY=BROWARD STAGE=Pre

COUNTY=PALM BEACH STAGE=Post COUNTY=PALM BEACH STAGE=Pre

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Hazard rates were also plotted for 24-month duration. Their underlying 

statistics are reported in Appendix C. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
B. SURVIVAL ANALYSIS USING PROPORTIONAL HAZARD 

FUNCTIONS (COX REGRESSION) 

The hazard function models discussed above provide a raw, or more 

descriptive, lifetime relationship between the occurrence of an event and time. 

With no clear indication on the underlying hazard distributions for each county 

pair and stage, a more general and less restrictive proportional hazard are adopted. 

The following set of Cox regression models examine the survival function of the 

same time and event, but treat recurrence and recidivism as repeatable events for 

each family. By not aggregating the events within a follow-up time frame, more 

information was available for model estimates. In addition, the explanatory 

variables included in the logistic regression were included, as well as three 

additional sets of variables, for a more comprehensive analysis. 

The three additional variable sets included in the following survival

functions are: 1) the effect of the previous report’s maltreatment severity on the 

likelihood of a recurrence event; 2) the effect of the previous report’s disposition 

severity on the likelihood of a recurrence event; and 3) the effect of the previous 

substantiated report on the likelihood of a recurrence event. Because recidivism

always involves substantiated reports, the survival analysis on recidivism includes 

on the two severity variables. 

Both severity variables are indexed on a 3-point scale of high, medium

and low. For maltreatment, high is considered abuse, medium is considered 

neglect, and low is considered threatened harm. These categories are modeled 

relative to the default category, which consists of cases with special circumstances 

such as custody issues or alternate jurisdiction. For disposition, high is 

considered court-ordered services with supervision, medium is court-ordered 

services without supervision, and low is voluntary or community services. These 

categories are modeled relative to the default category, which consists of cases 

that are dismissed or closed without services. 

The graphs on pages 75 through 79 represent survival curves for each 

model for each county pair by pre and post stages, plotting the log of survival 

estimates against time. The survival series graphs report on the cumulative risk of 

an event not occurring, or of family survival over time. 

To facilitate interpretation of the graphs, statistics on significant predictors

for recurrence and recidivism are provided for each county pair. The predictors 

are rank-ordered for both outcomes to explore differences between the county 

pairs. When the predictors are part of the severity indices on maltreatment and 

disposition, all three variables are included as a set because they are dichotomized 

presentations of categorical index variables. A full breakdown of survival 

estimates is available in Appendix D. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair I: Manatee-Lee (Graphs on p. 76)

T sur

the post stage ounties differ more in the 

ecidivism model during the pre stage, with Lee appearing to be more erratic. 

te.

t

With regard to 

e three-category disposition severity variable, low severity impacts negatively 

on recu igh

s

dictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 1: Manatee-Lee 

he vival rate for both counties remains constant and identical during 

for both recurrence and recidivism. The c

r

After day 400, both counties experienced a drastic decrease in the survival ra

As Table 37 indicates, however, the predictors are not necessarily the same for 

each outcome. Recurrence predictors are more numerous, with all Hispanic 

caretakers being the best predictor of recurrence. Interestingly, this variable is not 

significant at all as a predictor for recidivism, which could mean that Hispanics in

this are more at risk for being reported for maltreatment than they are of being 

substantiated for maltreatment. 

The three-category maltreatment severity variable is also a significan

predictor in recurrence without being significant for recidivism.

th

rrence and medium severity impacts very negatively on recidivism. H

severity disposition does not really impact either outcome. All severity categorie

are included in the table because they operate as parts of a singular variable, but 

those that are not significant are marked in yellow. Overall, disposition severity 

seems to act as a deterrent for both recurrence and recidivism. 

Table 37. Significant Pre

PAIR 1: 

Manatee- Lee

PAIR 1:

Manatee- Lee

RECURR

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

RECID 

Pr > Chi Hazard

Ratio 

Estimated 

Change in

Odds 

ALLHISPC 0.0181 0.771 22.9 MIXSEXC 0.0218 0.832 16.8 

SBINDXMD 0.0029 0.776 22.4 AVGVAGE <.0001 0.961 3.9 

SBINDXHI 0.0072 0.800 20.0 CHCOUNT 0.043 1.075 -7.5 

SBINDXLO

W 

0.0260 0.824 17.6 SEQ <.0001 1.323 

-32.3 

MOVEFLAG <.0001 0.831 16.9 DISPMD <.0001 1.479 -47.9 

MIXSEXC 0.0044 0.912 8.8 DISPHI 0.4607 0.928 7.2 

AVGVAGE <.0001 0.964 3.6 DISPLOW 0.0969 1.137 -13.7 

CHCOUNT 0.0078 1.043 -4.3 

VCOUNT 0.0027 1.065 -6.5 

NEGLECT 0.0421 1.070 -7.0 

DISPL

 

OW 0.0321 1.070 -7.0 

ABUSE 0.0166 1.097 -9.7 

MIXRACEC 0.0452 1.178 -17.8 

ALLMALEC 0.0148 1.178 -17.8 

SEQ <.0001 1.207 -20.7 

DISPHI 0.9908 0.999 0.1 

DISPMD <.0001 1.318 -31.8 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
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enter for Research on Youth and Social Policy University of Pennsylvania

78

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 2: Manatee-Sarasota (Graphs on p. 78)

The survival rates for recurrence and recidivism are constant and 

indistinguishable for the first 39 months in the post stage in both counties. The 

most severe rate change is for recurrence in the pre stage in both counties. There 

is a decreasing survival rate after 700 days for recurrence and after 450 days for 

recidivism in the pre stage. In the post stage, Manatee decreases after day 1300 

for recurrence and after day 1900 for recidivism. Table 38 demonstrates that in 

County Pair 2, the medium maltreatment severity category of the index is the 

greatest predictor of recurrence, with high and low severity not impacting the 

outcome significantly at all. Both medium and low disposition severity impact 

recurrence negatively, while only medium disposition severity impacts negatively 

on recidivism. Ethnicity does not play a part in recurrence, but the presence of all 

Hispanic caretakers in a substantiated report is the best predictor of recidivism. 

Table 38. Significant Predictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 2: ManateeSarasota 

PAIR 2: 

Manatee-Sarasota 

PAIR 2: 

Manatee-Sarasota 

RECURR

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

RECID 

Pr > Chiq Hazard 

Ratio 

Estimated 

Change in

Odds 

SBINDXMD 0.0091 0.772 22.8 ALLHISPV 0.0389 0.612 38.8 

MOVEFLAG <.0001 0.791 20.9 MIXSEXC 0.0171 0.837 16.3 

MIXSEXC <.0001 0.852 14.8 AVGVAGE <.0001 0.955 4.5 

AVGVAGE <.0001 0.961 3.9 MALTOTA

L 

0.0075 1.022 

-2.2 

MALTOTAL 0.0093 1.015 -1.5 SEQ <.0001 1.294 -29.4 

CHCOUNT 0.0138 1.047 -4.7 DISPMD 0.0049 1.364 -36.4 

DISPLOW 0.0104 1.098 -9.8 DISPHI 0.3056 0.904 9.6 

ABUSE 0.0073 1.131 -13.1 DISPLOW 0.1405 1.117 -11.7 

SEQ <.0001 1.197 -19.7 

DISPMD 0.0002 1.304 -30.4 

SBINDXHI 0.0649 0.838 16.2 

SBINDXLO

W 

0.1723 0.874 12.6 

 

DISPHI 0.3589 0.949 5.1 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
C

enter for Research on Youth and Social Policy University of Pennsylvania

80

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 3: Pinellas-Hillsborough (Graphs on p. 80)

The survival rates follow the same pattern here as in the first two county 

pairs, with the post stage in both counties being steadier the pre stage. There is no 

discrepancy in survival rates between counties and the rates remain constant for 

all four strata. This county pair, however, exhibits smaller percent changes in the 

odds although both recurrence and recidivism have more significant predictors in 

this model (Table 39). It is interesting that in this county pair, a family move is 

the best predictor of recurrence and the second best predictor of recidivism. 

Ethnicity also plays at role in both outcomes, with mixed ethnicity caretakers 

being the largest predictor of recidivism. Maltreatment severity, in all categories, 

impacts significantly on recurrence. Disposition severity, in all categories, 

impacts negatively on recurrence, while medium and low severity disposition 

impact negatively on recidivism. Family move, however, impacts only on 

recurrence. 

Table 39. Significant Predictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 3: PinellasHillsborough 

PAIR 3: 

PinellasHillsborough 

PAIR 3: 

PinellasRECURR Hillsborough 

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

RECID 

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

MOVEFLAG <.0001 0.831 16.9 MIXETHC 0.0081 0.782 21.8 

SBINDXMD 0.0006 0.847 15.3 MOVEFLA

G 

0.0002 0.860 

14.0 

MIXETHC 0.0155 0.879 12.1 MIXSEXC 0.0195 0.921 7.9 

ALLHISPV 0.0525 0.891 10.9 AVGVAGE <.0001 0.973 2.7 

SBINDXHI 0.0124 0.891 10.9 MALTOTA

L 

<.0001 1.023 

-2.3 

SBINDXLO

W 

0.0405 0.906 9.4 CHCOUNT <.0001 1.075 

-7.5 

MIXSEXC <.0001 0.910 9.0 DISPLOW 0.0184 1.087 -8.7 

AVGVAGE <.0001 0.970 3.0 MIXSEXV 0.0126 1.118 -11.8 

MALTOTAL <.0001 1.019 -1.9 NEGLECT <.0001 1.178 -17.8 

VCOUNT 0.0002 1.042 -4.2 DISPMD 0.0011 1.212 -21.2 

CHCOUNT <.0001 1.053 -5.3 SEQ <.0001 1.274 -27.4 

ABUSE 0.0052 1.065 -6.5 DISPHI 0.0267 1.107 -10.7 

NEGLECT <.0001 1.095 -9.5 

ALLMALEC 0.0071 1.118 -11.8 

DISPLOW <.0001 1.118 -11.8 

DISPHI <.0001 1.119 -11.9 

MIXRACEC 0.0077 1.134 -13.4 

ALLWHITE

V 

0.0055 1.146 -14.6 

 

SEQ <.0001 1.202 -20.2 

DISPMD <.0001 1.240 -24.0 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
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enter for Research on Youth and Social Policy University of Pennsylvania

82

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 4: Pasco-Lee 2 (Graphs on p. 82)

 This county pair exhibits decreasing rates for recurrence, particularly in 

the pre stage. The rates are more constant for both counties in the post stage. As 

Table 40 demonstrates, severity plays the largest role in predicting recurrence in 

this county pair; medium severity plays the largest role in predicting recidivism. 

Again, low and medium disposition severity impact negatively on both recurrence 

and recidivism. Unlike the first three county pairs, ethnicity plays no significant 

role in either outcome here. Unlike Pinellas-Hillsborough, family move 

significantly impacts on recidivism rather than recurrence. Again, the post stage 

in both counties exhibits steadier survival rates. 

 

Table 40. Significant Predictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 4: PascoLee 2 

 

PAIR 4: 

Pasco-Lee 2 

PAIR 4: 

Pasco-Lee 2 RECURR

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

RECID 

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

SBINDXMD 0.0035 0.773 22.7 SBINDXMD 0.0322 0.735 26.5 

SBINDXLO

W 

0.0070 0.786 21.4 MIXSEXC 0.0203 0.811 

18.9 

SBINDXHI 0.0299 0.832 16.8 AVGVAGE <.0001 0.961 3.9 

MIXSEXC 0.0001 0.886 11.4 MALTOTAL 0.0229 1.023 -2.3 

MOVEFLAG 0.0040 0.894 10.6 DISPLOW 0.0024 1.282 -28.2 

AVGVAGE <.0001 0.965 3.5 DISPMD 0.0100 1.298 -29.8 

VCOUNT <.0001 1.092 -9.2 SEQ <.0001 1.365 -36.5 

NEGLECT 0.0023 1.104 -10.4 SBINDXLO

W 

0.0474 0.757 

24.3 

DISPLOW 0.0007 1.112 -11.2 SBINDXHI 0.0921 0.796 20.4 

ABUSE <.0001 1.176 -17.6 DISPHI 0.8682 0.981 1.9 

SEQ <.0001 1.232 -23.2 

DISPMD <.0001 1.238 -23.8 

DISPHI 0.1646 1.072 -7.2 

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enter for Research on Youth and Social Policy University of Pennsylvania

84

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
County Pair 5: Broward-Palm Beach (Graphs on p.83)

For this county pair (Table 41), all Hispanic victims are the best predictor 

for both recurrence and recidivism. Medium severity predicts recurrence, while 

medium and high severity predict to recidivism. Medium disposition severity 

impacts negatively on both outcomes. Family move is significant only for 

recurrence. 

Table 41. Significant Predictors from Proportional Hazard Model for 

Recurrence and Recidivism for County Pair 5: Broward-Palm 

Beach 

PAIR 4: 

Pasco-Lee 2 

PAIR 4: 

Pasco-Lee 2 RECURR

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

RECID 

Pr > Chi Hazard 

Ratio 

Estimated 

Change in

Odds 

ALLHISPV <.0001 0.819 18.1 ALLHISPV 0.0014 0.740 26.0 

MOVEFLAG <.0001 0.86 14.0 SBINDXMD 0.0032 0.804 19.6 

SBINDXMD 0.0151 0.875 12.5 SBINDXHI 0.0111 0.830 17.0 

MIXSEXC 0.005 0.944 5.6 MIXSEXC 0.0170 0.903 9.7 

AVGVAGE <.0001 0.972 2.8 MOVEFLAG 0.0349 0.903 9.7 

MALTOTAL <.0001 1.018 -1.8 AVGVAGE <.0001 0.972 2.8 

VCOUNT 0.0004 1.043 -4.3 MALTOTAL <.0001 1.027 -2.7 

CHCOUNT <.0001 1.055 -5.5 VCOUNT 0.0504 1.040 -4.0 

NEGLECT <.0001 1.118 -11.8 CHCOUNT 0.0011 1.062 -6.2 

DISPMD 0.0014 1.131 -13.1 DISPMD 0.0064 1.183 -18.3 

ABUSE <.0001 1.149 -14.9 ALLMALEC 0.0355 1.238 -23.8 

ALLMALEC 0.0006 1.175 -17.5 SEQ <.0001 1.294 -29.4 

SEQ <.0001 1.244 -24.4 SBINDXLO

W 

0.4538 0.947 

5.3 

SBINDXHI 0.1145 0.919 8.1 DISPHI 0.9712 1.002 -0.2 

DISPLOW 0.5822 1.011 -1.1 DISPLOW 0.6671 1.018 -1.8 

SBINDXLO

W 

0.7378 1.018 -1.8 

 

DISPHI 0.8168 0.993 0.7 

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enter for Research on Youth and Social Policy University of Pennsylvania

86

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
C. MEDIAN LIFETIME ANALYSIS

The median lifetime, which estimates the point in time by which half the 

families will have experienced recurrence or recidivism, is a useful way to look at 

county pairs because it provides a specific duration estimate to compare across 

strata. The estimates were derived from the statistical output for the Cox 

regression models, which calculates time between events as number of days. To 

present a clearer picture of the median lifetime, the durations provided by the Cox 

regression were recalculated as months. As the duration was always presented as 

a range of days, the months were calculated conservatively using the first day in 

the range. Table 42 provides a breakdown of median times to survival in months 

for .50 of the population by county pair. 

Table 42. Median Lifetimes Estimates of Survival Probability in Months 

(p=.50) 

 

Survival Probability

Event: New 

Report

(Recurrence) 

Event: New 

Substantiated

Report

(Recidivism) 

 Pre Post Pre Post

Manatee 6.0 20.9 7.8 26.8 

PAIR 1 Lee 4.9 20.0 5.8 27.5 

Manatee 6.0 20.9 7.8 26.8 

PAIR 2 Sarasota 5.9 20.0 6.3 30.8 

Pinellas 32.6 53.8 9.9 39.5 

PAIR 3 Hillsborough 30.6 53.9 10.7 34.4 

Pasco 10.1 32.7 12.6 45.5 

PAIR 4 Lee2 9.1 29.1 12.9 32.1 

Broward 11.9 27.6 15.1 42.1 

PAIR 5 Palm Beach 9.7 25.9 10.8 36.4 

Sheriff Counties 9.8 27.4 11.7 39.2 

 Non-Sheriff Counties 9.3 26.1 10.7 35.0 

All counties increased median survival times for both recurrence and 

recidivism. The average median time to recurrence during the pre stage was 14.5 

months and 33.0 during the post stage. For recidivism, the average median time 

was 10.7 in the pre stage and 35.9 in the post stage13. Figure 18 illustrates the 

differences in increased time to recurrence among the county pairs and Figure 19

illustrates the same for recidivism. 

It appears that Pinellas and Hillsborough counties were most successful at 

increasing survival time to recurrence. Pasco and Broward demonstrates the 

largest increase in time to recidivism. When pre-post increases in median 

survival times are compared (Figure 20), the increases in time to recurrence are 

 

13 Pair 1 was left out of this average to avoid counting Manatee twice. The average refers to 8 

counties, 4 experimental and 4 comparison. 

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larger fo ime to recidivism. However, 

e difference between the two outcomes occurs in both experimental and 

compar

)

r six of the ten counties than the increase in t

th

ison counties, leaving little room to attribute the difference to the 

investigative transfer. 

Figure 18. Estimated Time to Recurrence in Months (p=.50

0

20

40

60

atee

Lee

atee

sota

llas

gh

sco

MaMaSar

Pine

lsbor

Br

lm B

nn

a

Hil ou

Pa

Lee2

owar

d

Pa each

PAIR 1 PAIR 2 PAIR 3 PAIR 4 PAIR 5

mont

hs

Pre

Post

Figure 19. Estimated Time to Recidivism in Months (p=.50)

0

10

20

30

50

at

Lee

Ma

natee

raso

Hillsborough

Lee2

40

Man eeSa ta

Pinellas

Pasco

Browar

d

Palm Beach

PAIR 1 PAIR 2 PAIR 3 PAIR 4 PAIR 5

Pre

Post

Figure 20. Pre-Post Increase in Survival Time in Months (p=.50) 

0

5

10

15

20

25

Ma

natee

Lee

Ma

natee

Sarasota

Pinellas

illsboroug

h

Pasco

Lee2

Browar

d

Palm Beach

H

PAIR 1 PAIR 2 PAIR 3 PAIR 4 PAIR 5

Recurrence

Recidivism

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 20 compares the pre-post difference between time to recurre

and time to recidivism for each county pair. With the exception of County

all county pairs demon

nce

Pair 3,

strate increases in the time between recurrence and 

ecidivism in the post stage. The Pinellas-Hillsborough pair is an anomaly in that 

e

ports themselves, yielding a negative difference pre and post. The data on this 

pair were checked repeatedly, but at the present time, there is no discernable 

explanation for this oddity. 

Figure 21. Pre-Post Difference between Time to Recurrence and Time to 

 Recidivism

r

their time between substantiated reports is shorter than their time between th

re

-25

-20

-15

-10

-5

0

5

10

15

20

Ma

natee

Lee

Ma

natee

Sarasota

Pi

nellas

Hillsborough

Pasco

Lee2

Broward

Palm Beach

PAIR 1PAIR 2PAIR 3PAIR 4PAIR 5

Pre

Post

Overall, the counties increased the median lifetime survival probabilities 

in the post stage and seem to have improved particularly with regard to 

recidivism. It is of course difficult to assess the situation in Pinellas-Hillsborough 

because of the unusual data associated with these counties. A full breakdown of 

survival probability estimates is available in Appendix E. 

S

The hazard function models illustrate, in a broad way, that the Sheriff may 

be having an influence in some of the counties on achieving a steady hazard rate, 

although all counties exhibit increases in the rate itself. 

Survival curves for recurrence are similar for all county pairs, with the 

post stage showing a more constant rate than the pre stage. The county pairs also 

share some significant predictors. Maltreatment and disposition severity are 

always significant, differing only in the level that is contributing an impact and 

the direction of the impact. Family move is shared, as is victim age and mixed 

sex of caretaker. Abuse as a type of maltreatment and the sequence of reports are 

also shared in the recurrence model, with both variables having a negative impact. 

D. UMMARY OF EVENT HISTORY ANALYSES 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Survival curves for recidivism are similar to those for recurrence, although 

the pre

at the

kely

et een the two. In terms of predictors, however, 

there is quite a lot a variety among the county pairs, particularly in which 

bilities, as all counties increased in this 

egard.

dictors are not the same. Victim age and mixed caretaker sex are still 

significant for all county pairs, but maltreatment severity’s impact is not shared. 

The negative impact of disposition severity is shared, however, and always

medium level. Sequence is shared and again has a negative impact. 

Overall, it seems that all county pairs are experiencing steady survival 

rates after the transfer of responsibility to the Sheriff’s Offices, making it unli

that there is an association b w

predictor is most salient. The law enforcement experiment did not seem to have 

an effect on median lifetime survival proba

r

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
III. PERFORMANCE OF SHERIFF’S OFFICES IN CHILD 

MALTREATMENT INVESTIGATIONS 

A. REPLICATION OF COUNTY PAIR ANALYSES F

V

OR

SHERIFF VS NON-SHERIFF COUNTIES 

nts and

only once, as part of Pair 4.

Odds Ratio Estimates: Substantiation

In concluding the quantitative data analyses for this report, the study 

replicated some of the county pair analyses as a two-way comparison between

aggregated experimental and comparison counties. To avoid duplicate cou

uneven weights, this comparison uses only four experimental and four 

comparison counties. Manatee was counted only once, as part of Pair 2. Lee was 

counted

A regression model was constructed for substantiation and illustrated that 

although the odds percentage was -20 in the post period overall, the odds 

percentage was 6.5 greater in the Sheriff counties and 7.7 greater in the 

interaction between the Sheriff counties and the post period (Table 43). 

 

Table 43. Change in Odds Ratio for Substantiation, Sheriff vs NonSheriff Counties 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq Point 

Estimate 

95 % Wald 

Confidence 

Intervals 

% 

Change 

in Odds

Ratio 

Post

Period -0.2232 <.0001 0.8 0.781 0.82 -20 

Sheriff 

Counties 0.0633 <.0001 1.065 1.04 1.091 6.5 

Interaction 0.0746 <.0001 1.077 1.042 1.114 7.7 

 

Change in Percentage of Reports: Substantiation, Recurrence, and 

Recidivism

Looking at the situation from a change in percentage perspective (Figure

22), it seems that the Sheriff counties are experiencing less of a decrease in 

reports substantiated, less of an increase in reports representing recurrence, and 

less of a decrease in reports representing recidivism in the post stage. This 

indicates that they are performing better in substantiation and recurrence than the 

non-Sheriff counties, but not quite as well with regard to recidivism. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figu e 22. Change in Percentage of Reports: Substantiation

Recidivism, Sheriff vs Non-Sheriff Counties 

r , Recurrence,

-10

-5

0

5

10

Sheriff -5.37 1.57 -1.29

No .63

rr %Recid

n-Sheriff -5.58 5.25 -0

% Subs % Recu

Effect Size Comparisons: Severity

Figure 23 demonstrates that the investigative transfer has had no policy

pact on m

Fig arison: Maltreatment and Disposition 

Severity, Sheriff and Non- Sheriff Counties 

relevant im altreatment or disposition severity, although the Sheriff 

counties were more successful in decreasing the latter. 

ure 23: Effect Size Comp

-2

-1

0

1

Sheriff 0.19 -1.57

Non-Sheriff 0.13 0.01

Maltreatment Severity Disposition Severity

losing. It appears that the Sheriff counties greatly increased the duration on both 

utcomes. 

 

Effect size comparisons were calculated for duration as well as severity.

Figure 24 demonstrates the policy-relevant impact all counties on both time to

finding and time to case closing and services opening, although the impact was 

not in the desired direction. Figure 25 compares the Sheriff and non-Sheriff 

counties on the pre-post change in the mean number of days to finding and case 

c

o

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 24. Effect Size Comparison: Time to Finding and Time to 

Closing/Open Service, Sheriff vs Non-Sheriff Counties

0

0.2

0.4

0.6

Sheriff 0.44 0.40

Non-Sheriff 0.30 0.25

Time to Finding Time to Closing

Figure 25. Mean # of Days to Finding and Closing/Open Service, Sheriff 

vs Non-Sheriff Counties 

0

10

20

30

40

50

Sheriff 46.04 45.16

Non-Sheriff 16.40 13.47

Time to Finding Time to Closing

 

Hazard Function Analysis and Cox Regression

The recidivism graphs on page 92 can be viewed interpretively in the same 

anner as the county pair graphs. Only the smooth hazard graph is shown 

ly indicates that the hazard decreases gradually in the pre stage 

m

because it clear

and increases slightly in the post stage for both Sheriff and non-Sheriff counties. 

The survival curve confirms that the situation remains basically the same even 

when adding covariates and repeated measures, although the decrease is steeper

pre stage. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Sheriff vs Non-sheriff County Recidivism Hazard

18 Months Follow-up

Negative Log S

DF 0.00

0.25

0.50

0.75

1.00

1.25

DUR18

0 100 200 300 400 500 600

STRATA: COUNTY=NONSHERIFF COUNTY STAGE=Post COUNTY=NONSHERIFF COUNTY STAGE=Pre

COUNTY=SHERIFF COUNTY STAGE=Post COUNTY=SHERIFF COUNTY STAGE=Pre

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Median Lifetime Analysis

 Figure 27 provides the median lifetime survival probability estimates pre 

and post for the Sheriff and non-Sheriff counties. It is clear that both Sheriff and 

non-Sheriff counties experienced large increases in survival times for both 

recurrence and recidivism. 

Figure 27. Median Lifetime Estimates for Survival Probably in Months 

(p=.50), Sheriff vs Non-Sheriff Counties.

0

10

20

30

40

50

Recurrence Recidivism Recurrence Recidivism

Sheriff Non-Sheriff

Pre

Post

Aggregating the Sheriff and non-Sheriff counties confirmed the picture 

presented by the county pair analyses. When there was improvement over time, 

the improvement usually occurred for all counties. It does not seem that any 

significant change can be attributed to the transfer of responsibility to the 

Sheriff’s Offices. However, the State of Florida began measuring the 

performance of child protective investigation agencies statewide a year ago, using 

their new Home Safe Net data system. A summary of the results for year 2003-

2004 follows. 

B. FLORIDA’S STATEWIDE PERFORMANCE INDICATORS 

Each month, performance of the investigating agencies is tracked 

according to twelve indicators:

1. % of investigations commenced on time (within 24 hours) 

2. of victims seen, % of victims seen within 24 hours 

3. % of CSA (initial) submitted within 48 hours of receiving report 

4. % of supervisor first review within 72 hours of CSA initial submitted 

5. % of supervisor first review agreement with overall child safety 

assessment 

6. % of second party first review within 72 hours of being referred 

7. % of second party first review agreement with supervisor 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
8. ispo submitted within 45 days of being received 

9. view within 3 days

10. % of supervisor agreement with first submitted recommended dispo 

ds,

reported leaderboard statistics for the twelve month 

period from August, 2003, to July, 2004 for the leaderboard position (overall 

rank) and the indicators regarding opening and closing investigations on time. 

r

the twelve-mo ed top with Broward 

(Sheriff’s) second. 

Figure 28. Overall Ranking for Florida’s Investigative Child Welfare 

 Agencies* 

D

% of supervisor first dispo re

11. % of investigations completed (closed) by supervisor in 60 days 

To evaluate the performance of the Sheriff’s Offices by state standar

this study analyzed the state

Figure 28 indicates that when rankings on individual indicators are averaged ove

nth period, Seminole County (Sheriff’s) rank

Average Leaderboard Position (overall rank)

1.00

2.17

3.17

5.42

6.75

7.75

7.75

8.58

8.92

9.75

10.33

10.75

District 04 - CW

District 01 - CW

District 08 - CW

Suncoast Region - Pasco SO

Suncoast Region - CW

Suncoast Region - Manatee SO

District 03 - CW

District 15 - CW

Distr

Dist

11.83

13.00

14.33

16.42

District 07 - Seminole SO

District 10 - Broward SO

District 12 - CW

District 02 - CW

ict 09 - CW

rict 14 - CW

Suncoa gion - Pinellas SO

Dist

Dist

st Re

15.92

16.08

rict 11 - CW

rict 13 - CW

District 07 - CW

ure 29),

Sem twelve months. Pasco, 

Ma 4

(Ma t las

Nov May

2004 and then dipped to 13 by July 2004. 

Looking at the Sheriff’s counties alone for each month (Fig

inole was ranked #1 and Broward #2 for eleven of the

natee, and Pinellas were more variable ranging from a high ranking of

na ee in June and July 2004) to a low of 16 (Manatee October 2003, Pinel

ember 2003 and February 2004). Pasco reached a peak of rank #5 in

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 29. Ranking for Sheriff Counties Only

Leaderboard position - SO counties

0

1

2

3

4

5

6

7

8

AugSep-0

Oct-0

NovDec-0

Jan-04Feb

Mar-04Apr-04

May

Jun-0

Jul-0

9

10

14

15

16

17

03

3

3

03

3

-04

-04

4

4

11

12

13

District 07 - Seminole SO District 10 - Broward SO Suncoast Region - Manatee SO

Suncoast Region - Pasco SO Suncoast Region - Pinellas SO

Comparing the aggregate of Sheriff’s Office (SO) and non-Sheriff’s 

Office (child welfare; CW) counties (Figure 30), SO counties ranked higher than 

CW counties every month. Looking more closely at particular indicators, Figure 

31 indicates that Seminole is again ranked number one for commencing 

investigations on time (within 24 hours). Broward and Manatee counties occupy 

ranks three and four, respectively, compared with the other counties. 

For timely completion of investigations (within 60 days) (Figure 32), 

Seminole drops to an average rank of 12.75. Pasco, which had an average rank of 

9.67 for commencing investigations, also shares this rank. Broward County’s 

rank for closing (4.50) was also lower than their rank for commencing 

investigations (2.92). Manatee and Pinellas counties performed better on timely 

losing of investigations (4.33 and 6.08, respectively) than for opening (6.08, 

.58).

c

8

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 30. Comparison of Average Ranking, Sheriff vs Non-Sheriff 

Counties

Leaderboard Position Average by County Type

0

2

4

6

8

10

12

Aug-03Sep-03

Oct-03

Nov-03

Dec-03

Jan-04

Feb-04Mar-04

Apr-04

May-04

Jun-04

Jul-04

AVERAGE CW AVERAGE SO

Figure 31. Average Rank for Investigations Commenced on Time

Investigations Commenced on Time (Average Rank

1.08

2.83

2.92

District 07 - Seminole SO

District 12 - FS

District 10 - Broward SO

Suncoa gion - Manatee So

)

6.08

10.50

11.25

11.58

14.08

14.17

15.33

16.08

District 08 - FS

District 01 - FS

District 13 - FS

District 09 - FS

District 14 - FS

District 11 - FS

District 15 - FS

st Re

8.25

8.50

8.58

8.92

9.50

9.67

10.17

Suncoast Region - FS

District 04 - FS

Suncoast Region - Pinellas SO

District 03 - FS

District 02 - FS

Suncoast Region - Pasco SO

District 07 - FS

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Figure 32. Average Rank for Investigations Completed in 60 Days 

Investigations Completed by 60 Days (Average Rank)

1.17

2.67

3.33

4.33

4.50

6.08

7.67

8.83

9.50

11.75

11.92

12.75

12.75

12.83

13.42

14.08

15.25

16.50

District 04 - FS

District 07 - FS

District 02 - FS

Suncoast Region - Manatee So

District 10 - Broward SO

Suncoast Region - Pinellas SO

District 12 - FS

District 01 - FS

District 03 - FS

District 11 - FS

District 09 - FS

District 07 - Seminole SO

Suncoast Region - Pasco SO

District 13 - FS

District 14 - FS

District 15 - FS

District 08 - FS

Suncoast Region - FS

C. SUMMARY OF FINDINGS ON PERFORMANCE OF

SHERIFF OFFICES 

With regard to report substantiations, a regression model revealed that the 

odds percentage was 7.7 greater in the post-period in the Sheriff’s counties. An 

analysis of percentage changes in substantiation, recurrence and recidivism

indicated that the Sheriff counties are performing better in substantiation and 

recurrence than the non-Sheriff counties, but not quite as well with regard to 

recidivism. The investigative transfer has had no policy relevant impact on 

maltreatment or disposition severity, although the Sheriff counties were more 

successful in decreasing the latter. With regard to duration of investigation and 

length of time to case opening for service, all counties experienced a negative 

policy-relevant impact all counties on both time to finding and time to case 

closing and services opening. The Sheriff counties appear to be greatly increased 

the mean # of days on both outcomes. 

Event history analyses illustrate that the hazard for recidivism decreases 

gradually in the pre stage and increases slightly in the post stage for both Sheriff

and non-Sheriff counties. Both Sheriff and non-Sheriff counties experienced 

large increases in median survival times for both recurrence and recidivism, 

making it unlikely that either hazard or survival are impacted by the transfer of 

investigative responsibility. Using Florida’s statewide performance indicators as a 

easure of success, the Sheriff counties consistently outperform the non-Sheriff 

ounties on all 11 measures. Overall, Broward outperforms all counties in this 

m

c

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
study (Table 44). However, with the exception of Broward, the comparison 

Table 44. Ranking for Experimental and Comparison Counties 

1 Broward 

counties outperform the other experimental counties. 

2 Lee (District 8)

3 Pasco 

4 Sarasota, Hillsborough (Suncoast CW) 

5 Manatee 

6 Palm Beach (District 9) 

7 Pinellas 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
IX. SUMMARY COMPARISON ACROSS MEASURES

able 45 s the county pairs across analytic measures and 

identifies those counties that succeeded in achieving a statistically significant or 

policy-relevant desired outcome. All counties shared three of these measures: 1)

a decre e in the evel maltreatment severity; 2) 

an increase in survival rates for recurrence and time to recurrence; and 3) an 

increase in survi and time to recidivism. Most of the 

counties decreased the time between a report being received and a case being 

losed for investigations and simultaneously opened for service. The most

desirable indicator of successful improvement in child safety, as noted earlier, is a 

decrease in recurrence and recidivism, so in that sense, the safety situation seems 

to be improving in the post stage. However, as it is improving in all counties, it is 

not an indicator of the success of the investigative transfer. 

Table 45. County Pair Comparison Across Analytic Measures

A. County Comparison Across Analytic Measures 

T compare

as percent of reports with high index l

val rates for recidivism

c

Desired Outcome Pair 1 Pair 2 Pair 3 Pair 4 Pair 5 

M L M S Pin H Pas L2 B PB 

Increase in % 

Substantiated X 

Increase in Odds 

Percentage of

Substantiation 

X X X 

Impact on 

Substantiation 

(ES) 

Decrease in % 

High Index 

Maltreatment

Severity 

X X X X X X X X X X 

Impact on 

Maltreatment

Severity (ES) X X 

Decrease in % 

High Index 

Disposition 

Severity 

 X X X 

Impact on 

Disposition 

Severity (ES) X X X 

Decrease Time to 

Finding (ES) X X X X X X X 

Decrease Time to 

Close/Open Svc 

(ES)

 X X X X X X 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Decrease in % 

X Recurrence X X 

Decrease in % 

Recidiv ism X X X 

Decrease in 

Hazard for 

Recurrence 

Decrease in 

Hazard for 

Recidivism

 

Increase in

Survival Rate for 

Recurrence 

X X X X X X X X X X 

Increase in

Survival Rate for 

Recidivism

X X X X X X X X X X 

Increase Survival 

Time to 

Recurrence

(months) 

X X X X X X X X 

Increase Survival 

Recidivism

Data 

X X X 

Questionable 

Time to X X X X X

(months) 

Sheriff vs No -She f Acr ss All easu es

Tabl compares the Sheriff and Non-Sheriff counties across 

a res and statewide performance indicators. The Sheriff counties 

outperform all non-Sheriff counties only in odds of a report being substantiated, 

i osition everi , and atewid icators. However, when the 

counties in this study are ranked, the non-Sheriff counties outperform the Sheriff 

counties, with the exception of Broward. Otherwise, the significance and/or 

i transfe f inv igati resp ibili appe be n ligib

T County Pair Comparison Across Analytic Measures

B. n rif o M r

nalytic measu

e 46

mpact on disp s ty st e ind

mpact of the r o est ve ons ty ars eg le.

able 46.

Desired Outcome Sheriff Non-Sheriff 

Increase in Odd

Substantiatio

s Percentage of

n 

X 

Increase in % Substantiation 

Impact on Maltreatment Severity (ES) 

Impact on Disposition Severity (ES) X 

 

Decrease Time to Finding (ES) X X 

Decrease Time to Close/Open Svc (ES) X X 

Decrease in % Recurrence 

Decrease in % Recidivism X X 

Decrease in Hazard for Recidivism X X 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Increase in Survival Rate for Recidivism X X 

Increase Survival Time to Recurrence X X (months) 

Increase Survival Time to Recidivism X X (months) 

Overall Ran

Indicators (al

king on Florida St tewide 

l counties) X a 

Overall Rank

Indicators (e

counties) 

ing on Florida Statewide 

xperimental and comparison X 

COMPARISON OF FINDINGS FROM ORIGINAL AND 

UPP ME AL UDIES 

ngs from this supplemental study confirm, to some extent, the 

findings of the original study. More rigorous analyses supported the original 

f t the investigative transfer had little impact on recurrence and 

r ugh the analyses did clarify that that there was more convergence 

a l counties th had en p ious all counties improved 

i reas suc inc sed viva es. With regard to the or

es for perpetrators, this study was able to 

stablish to some extent the percentage of perpetrators likely to experience 

riminal sanctions (35.9%) in Broward County, at least over the last year. 

Unfortu ly, at the state level, it 

is represented a difference due to the 

ther

sues evaluated in the original study such as implementation fidelity and 

eas.

X N

w, it is fair to say that the seco

report indicate that the transfer of investigative responsibility to law enforcement 

h d impact. s important to remember, however, 

t orcement is still new, althou the difficulties 

a eavor seem to ha been overco

i pective of the state-identified performance 

indicators, it is clear the Sheriff’s ffices are oing a uniform

i eatment. The initial fears of stakeholders that law 

e mental effect on the system, that police would not 

be sensitive to the com the issues af amilies in the system, that 

C. 

S LE NT ST

The findi

indings tha

ecidivism, altho

mong al

n discrete a

an

h as

be

rea

rev

sur

ly revealed, i.e. 

l tim iginal 

unanswered question regarding outcom

e

c

nate due to the change in data collection procedures

was not possible to ascertain whether th

transfer of investigative responsibility. This study was able to determine, 

however, that a pilot study monitoring the link between child welfare and criminal 

outcomes was feasible given appropriate funding. This study also found that the

Sheriff counties consistently outperformed the DCF counties on a series of 11

performance indicators tracked regularly by the state if compared statewide. If 

only the counties in this study are compared, the non-Sheriff counties 

outperformed with the exception of Broward. As this study did not cover o

is

investigator perspectives, there are no supplemental findings in these ar

. CONCLUSIO

For no ndary data analyses presented in this 

as not had the desired or expecte It i

hat the experiment with law enf gh

ssociated with the new end ve me. Viewing the 

nvestigative transfer from the pers

O d ly good job in 

nvestigating child maltr

nforcement would have a detri

plexity of fecting f

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
t mergency shelter and foster care remain 

unrealized. Site visits to Broward County re aled that the O is firmly 

e d in the Child Protective Supervision system, comm

wherever possible, and open to participating in a pilot study linking their work 

w t. For a researcher who has been trying to 

generate interest in linking the two systems and to convince agencies of its 

i ork with on this issue, pos bly because law

e inal matters and has only lately become

i involved with child welfare. The researchers and BSO, as well as the 

ourt itself, seem to agree that institutionalizing a feedback loop would be 

eneficial to all concerned in terms of policy and practice. 

With re studies indicate that it may make

no difference which agency conducts child maltreatment investigations. It may 

make a

s in

s

ns and

here would be radical increases in e

ve BS

ntrenche itted to improving 

ith the work of the criminal cour

mportance, the BSO is easier to w

nforcement usually deals with crim

ntimately

si

c

b

gard to policy and practice, both

difference, however, that the agency conducting investigations is not the

same agency that delivers services. Broward County, along with most countie

Florida, recently privatized child welfare services and transferred all courtordered service cases to a lead agency, ChildNet. The relationship between BSO 

and ChildNet appears to be healthy, although the relationship is still new and may 

need time to reach peak efficiency. The Principal Investigator for this study ha

established a working relationship with ChildNet, as well as an ongoing 

relationship with BSO, so that she is well suited to monitor the link between 

investigative and service outcomes, as well as the link between investigatio

criminal sanctions. Ideally, the well-being of the children and families in the 

child welfare system would be enhanced if care were taken to view their wellbeing from such an ecological perspective.

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
References

Allison, P. D. (1984). Event history analysis: Regression for longitudinal event data. 

Newbury Park, CA: Sage Publications. 

Besharov, D. (1987). Statement before the Select Committee on Children, Youth and 

Families. The American Institute for Publics Policy Research: Washington, D.C. 

Besharov, D. (1993). Overreporting and underreporting are twin problems. In. R.J. Gelles 

& D. Loseke (Eds.) Current Controversies on Family Violence. Newbury Park, CA: 

Sage. 

Besharov, D. with Laumann, A. (1996). Child abuse reporting. Society, 33 (4), 40-46. 

Campbell, D. and Stanley, J. (1963). Experimental and Quasi-Experimental Designs for

Research. Chicago: Rand McNally College Publishing Co. 

Child Protective Services Annual Statistical Report, Fiscal Year 1997-98 (to be 

published). Florida Department of Children and Families. 

Cohen, J. (1988). Statistical power analysis for the behavioral services. Hillsdale, NJ: 

Lawrence Erlbaum Associates, Publishers. 

Costin, L. B., Karger, H.J., & Stoesz, D. (1996). The Politics of Child Abuse in America. 

New York: Oxford University Press.. 

Coyle, S.L., Boruch, R. F., and Turner, C.F. (Eds.) (1991). Evaluating AIDS Prevention

Programs. Washington, D.C: National Academy of Science Press. 

. 

Gelles, R. (1996). The Book of David: How Preserving Families Can Cost Children’s 

Lives. New York, NY: Basic Books. 

Grayson, J. (ed). (1994). Joint investigation: A multidisciplinary approach. Virginia Child 

Protection Newsletter, V44, 1, 3-7, 16. 

Hammond, C.B., Lanning, K.V., Promisel, W., Shepherd, J.R., Walsh, B. (1997). Law 

Enforcement Response to Child Abuse. Washington, D.C.:National Institute of 

Justice/NCJRS. 

Kamerman,S. and Kahn, A. (1990). Social services for children, youth, and families in 

the United States. Children and Youth Services Review. 12,1/2, pp 1-184.

Lindsey, D. & Hawkins, W. (1994). Should the police have greater authority in 

investigating cases of suspected child abuse? In E. Gambrill & T. Stein (eds.), 

Controversial Issues in Child Welfare. Boston, MA: Allyn and Boston. 

105

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Lindsey, D. (1994). The Welfare of Children. New York, NY: Oxford University Press. 

Maguire, E.R. (1993). Professionalization of police in child sexual abuse cases. Journal 

of Child Sexual Abuse, 2 (3), 107-116. 

McDowall, D., McCleary, R., Meidinger, E., and Hay, R. (1980). Interrupted Time Series

Analysis. Newbury Park, CA: Sage Publications. 

National Council on Child Abuse and Neglect. (1998). Fact Sheet, http://www.calib. 

com/nccanch/ pubs/infact.htm.

National Council of Child Abuse. (1996). Child Maltreatment 1996: Reports from the 

States to the National Child Abuse and Neglect Data System. 

National Research Council. (1998). Violence in Families: Assessing Prevention and 

Treatment Programs. Washington, D.C.: National Academy Press. 

Pelton, L. (1998), Commentary. The Future of Children, Vol. 8, No. 1, 126-129. 

Pelton, L. (1993). Enabling public child welfare agencies to promote family 

preservation. Social Work, 38 (4), 491-493. 

Pelton, L. (1991). Beyond permanency planning: Restructuring public child welfare 

agencies. Social Work. 36,4, pp. 337-343. 

Pressman, J. and Wildavsky, A. (1973). Implementation: How Great Expectations in 

Washington are Dashed in Oakland. Berkeley, CA: University of California Press. 

Rossi, P. and Freeman, H. (1993). Evaluation: A Systematic Approach (Fifth Edition). 

Newbury Park, CA: Sage Publications. 

Sheppard, D.I. and Zangrillo, P.A. (1996). Coordinating investigations of child abuse. 

Public Welfare, 54 (1), 21-32. 

Sherman, L. & Berk, R. (1984). The specific deterrent effects of arrest for domestic 

assault. American Sociological Review, 49, 261-272. 

Williams, W. (1980). The Implementation Perspective. Berkeley, CA: University of 

California Press. 

 

Zaslow, M.J., McGroder,S.M., and Moore, K.A. (2000). Impacts on young children and 

their families two years after enrollment: Findings from the child outcomes study. A 

Summary Report from the National Evaluation of Welfare-to-Work Strategies @ 

http://aspe.hhs.gov/hsp/NEWWS/child-outcomes/summary.htm. Washington, D.C.: 

Department of Health and Human Services 

106

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX A 

Population Census (2000) Data for 8 Counties 

County Pair Data on Caretakers, Victims and Children 

107

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Population Characteristics for 8 counties 

Pinellas Hillsborough Broward Palm Beach 

Experimental Comparison Experimental Comparison

Total Pop. 921,482 998,948 1,623,018 1,131,184

 

% White 85.9% 75.2% 70.6% 79.1%

 

Med. Household Income $37,111 $40,663 $41,691 $45,062 

 

Children Under 18 19.3% 25.3% 23.6% 23.2%

 

% Persons below 

Poverty 

10.0% 12.5%

11.5% 9.9%

 

# Maltreatment Reports 7725 9632 12376 8988

Census 2000

Florida DCF Annual 2000-2001 Report

108

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Caretaker and Children Data on County Pairs 

SHERIFF 

 Broward Manatee Pinellas Pasco 

CARETAKERS 

Age (26-35) 39.9 42.47 40.63 42.81

Race (all white) 55.52 76.91 75.15 94.32

Ethnicity (all non-Hispanic) 89.24 91.92 97.26 95.77

Family Composition 

Single Caretaker 16.68 17.10 17.39 13.58

Female Single Caretaker 81.91 76.15 83.5 80.29

 

DCF 

Palm Beach Lee Hills Lee 

Age (26-35) 40.29 42.35 41.84 41.81

Race (all white) 62.55 73.29 67.74 73.7

Ethnicity (all non-Hispanic) 85.86 88.83 88.19 88.41

Family Composition 

Single Caretaker 13.94 16.29 20.52 15.13

Female Single Caretaker 82.49 81.1 84.33 81.91

 

SHERIFF 

 Broward Manatee Pinellas Pasco 

Mean # per Report 

victims 1.6 1.6 1.6 1.7

other children 0.3 0.4 0.4 0.4

 

DCF 

Palm Beach Lee Hills Lee 

Mean # per Report 

victims 1.7 1.7 1.7 1.7

other children 0.4 0.5 0.4 0.4

*Sarasota data not able to be processed for this

report. 

109

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX B 

Odds Ratio for Substantiation 

by County and County Pairs 

110

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 1: Manatee County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.6036 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1562 <.0001 1.169 1.145 1.193 16.9 

ABUSE -0.1826 0.0008 0.833 0.749 0.927 -16.7 

NEGLECT -0.2077 <.0001 0.812 0.734 0.900 -18.8 

AVGCTAGE -0.00349 0.1598 0.997 0.992 1.001 -0.3 

AVG_VAGE -0.011 0.0178 0.989 0.98 0.998 -1.1 

ALLWHITEC -0.2031 0.0486 0.816 0.667 0.999 -18.4 

MIXRACEC 0.037 0.7549 1.038 0.823 1.309 3.8 

ALLWHITEV 0.0599 0.553 1.062 0.871 1.294 6.2 

MIXRACEV 0.1663 0.4224 1.181 0.787 1.773 18.1 

ALLHISPC 0.182 0.1823 1.200 0.918 1.568 20 

MIXETHC 0.1988 0.1198 1.220 0.95 1.567 22 

ALLHISPV -0.1148 0.3235 0.892 0.71 1.120 -10.8 

MIXETHV -0.0407 0.8421 0.960 0.643 1.433 -4 

ALLMALEC -0.0817 0.3794 0.922 0.768 1.106 -7.8 

MIXSEXC 0.382 <.0001 1.465 1.331 1.613 46.5 

ALLFEMV -0.0162 0.7172 0.984 0.901 1.074 -1.6 

MIXSEXV 0.085 0.2139 1.089 0.952 1.245 8.9 

CHCOUNT -0.069 0.0028 0.933 0.892 0.976 -6.7 

VCOUNT -0.2459 <.0001 0.782 0.731 0.837 -21.8 

MOVEFLAG 0.1979 0.0207 1.219 1.031 1.441 21.9 

POST -0.346 <.0001 0.708 0.646 0.775 -29.2 

111

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 1: Lee County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept -0.4486 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limites 

Odds 

(percentage) 

MALTOTAL 0.0564 <.0001 1.058 1.043 1.073 5.8 

ABUSE 0.0113 0.8141 1.011 0.92 1.111 1.1 

NEGLECT -0.1217 0.0092 0.885 0.808 0.97 -11.5 

AVGCTAGE 0.00241 0.3002 1.002 0.998 1.007 0.2 

AVG_VAGE -0.0203 <.0001 0.980 0.972 0.988 -2 

ALLWHITEC -0.261 0.0159 0.770 0.623 0.952 -23 

MIXRACEC 0.0697 0.5124 1.072 0.870 1.321 7.2 

ALLWHITEV -0.2567 0.0142 0.774 0.630 0.950 -22.6 

MIXRACEV -0.1656 0.3744 0.847 0.588 1.221 -15.3 

ALLHISPC 0.2781 0.013 1.321 1.060 1.645 32.1 

MIXETHC 0.1343 0.1824 1.144 0.939 1.393 14.4 

ALLHISPV -0.0341 0.7366 0.967 0.793 1.179 -3.3 

MIXETHV 0.1239 0.4388 1.132 0.827 1.549 13.2 

ALLMALEC 0.1603 0.0912 1.174 0.975 1.414 17.4 

MIXSEXC 0.509 <.0001 1.664 1.522 1.818 66.4 

ALLFEMV 0.0433 0.2892 1.044 0.964 1.131 4.4 

MIXSEXV 0.0793 0.1827 1.083 0.963 1.217 8.3 

CHCOUNT -0.0553 0.0076 0.946 0.909 0.985 -5.4 

VCOUNT -0.1287 <.0001 0.879 0.830 0.931 -12.1 

MOVEFLAG 0.266 0.0006 1.305 1.120 1.519 30.5 

POST -0.5587 <.0001 0.572 0.527 0.62 -42.8 

112

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 1: Manatee-Lee Interaction

Maximum Likelihood Estimates Odds Ratio Estimates 

 Estimate Pr > ChiSq 

Intercept -0.4427 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0903 <.0001 1.094 1.082 1.107 9.4 

ABUSE -0.0732 0.0414 0.929 0.866 0.997 -7.1 

NEGLECT -0.1548 <.0001 0.857 0.800 0.917 -14.3 

AVGCTAGE -0.00028 0.8708 1.000 0.996 1.003 0 

AVG_VAGE -0.0164 <.0001 0.984 0.978 0.99 -1.6 

ALLWHITEC -0.2363 0.0016 0.790 0.682 0.914 -21 

MIXRACEC 0.0622 0.4354 1.064 0.910 1.244 6.4 

ALLWHITEV -0.1146 0.1162 0.892 0.773 1.029 -10.8 

MIXRACEV -0.00617 0.9638 0.994 0.761 1.298 -0.6 

ALLHISPC 0.2441 0.0047 1.276 1.078 1.512 27.6 

MIXETHC 0.1648 0.0358 1.179 1.011 1.375 17.9 

ALLHISPV -0.0601 0.4306 0.942 0.811 1.094 -5.8 

MIXETHV 0.0468 0.7071 1.048 0.821 1.338 4.8 

ALLMALEC 0.0237 0.7219 1.024 0.899 1.167 2.4 

MIXSEXC 0.4559 <.0001 1.578 1.479 1.683 57.8 

ALLFEMV 0.0193 0.5241 1.019 0.961 1.082 1.9 

MIXSEXV 0.0965 0.0297 1.101 1.01 1.201 10.1 

CHCOUNT -0.0629 <.0001 0.939 0.911 0.968 -6.1 

VCOUNT -0.1741 <.0001 0.84 0.805 0.877 -16 

MOVEFLAG 0.2311 <.0001 1.260 1.126 1.410 26 

POST -0.5819 <.0001 0.559 0.516 0.606 -44.1 

MANATEE 1.0718 <.0001 2.921 2.629 3.244 192.1 

MANAPOST 0.2612 <.0001 1.299 1.151 1.465 29.9 

113

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 2: Sarasota County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.2698 0.0387

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1509 <.0001 1.163 1.138 1.189 16.3 

ABUSE -0.0687 0.244 0.934 0.832 1.048 -6.6 

NEGLECT -0.0176 0.7599 0.983 0.878 1.100 -1.7 

AVGCTAGE -0.00439 0.1055 0.996 0.99 1.001 -0.4 

AVG_VAGE -0.0125 0.0146 0.988 0.978 0.998 -1.2 

ALLWHITEC -0.0551 0.7077 0.946 0.709 1.262 -5.4 

MIXRACEC 0.254 0.0912 1.289 0.96 1.731 28.9 

ALLWHITEV -0.162 0.2525 0.850 0.644 1.122 -15 

MIXRACEV 0.0387 0.8799 1.039 0.629 1.716 3.9 

ALLHISPC 0.3486 0.0786 1.417 0.961 2.090 41.7 

MIXETHC 0.5556 0.0053 1.743 1.179 2.576 74.3 

ALLHISPV -0.3788 0.0332 0.685 0.483 0.970 -31.5 

MIXETHV -0.3375 0.2876 0.714 0.383 1.329 -28.6 

ALLMALEC -0.0641 0.5702 0.938 0.752 1.170 -6.2 

MIXSEXC 0.3446 <.0001 1.411 1.272 1.566 41.1 

ALLFEMV 0.092 0.0564 1.096 0.998 1.205 9.6 

MIXSEXV 0.1841 0.0166 1.202 1.034 1.397 20.2 

CHCOUNT -0.1218 <.0001 0.885 0.837 0.937 -11.5 

VCOUNT -0.2824 <.0001 0.754 0.694 0.819 -24.6 

MOVEFLAG 0.2355 0.0192 1.266 1.039 1.541 26.6 

POST -0.5683 <.0001 0.566 0.512 0.627 -43.4 

114

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 2: Manatee-Sarasota Interaction 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.2489 0.0079

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1538 <.0001 1.166 1.149 1.184 16.6 

ABUSE -0.1321 0.0009 0.876 0.811 0.947 -12.4 

NEGLECT -0.1209 0.0017 0.886 0.822 0.956 -11.4 

AVGCTAGE -0.00393 0.0314 0.996 0.993 1.000 -0.4 

AVG_VAGE -0.0118 0.0006 0.988 0.982 0.995 -1.2 

ALLWHITEC -0.1606 0.0555 0.852 0.723 1.004 -14.8 

MIXRACEC 0.1157 0.2121 1.123 0.936 1.346 12.3 

ALLWHITEV -0.0159 0.8463 0.984 0.838 1.156 -1.6 

MIXRACEV 0.134 0.404 1.143 0.835 1.567 14.3 

ALLHISPC 0.235 0.0358 1.265 1.016 1.575 26.5 

MIXETHC 0.3096 0.004 1.363 1.104 1.683 36.3 

ALLHISPV -0.1863 0.0545 0.830 0.686 1.004 -17 

MIXETHV -0.1281 0.4514 0.880 0.630 1.228 -12 

ALLMALEC -0.0727 0.3082 0.930 0.809 1.069 -7 

MIXSEXC 0.366 <.0001 1.442 1.344 1.547 44.2 

ALLFEMV 0.0355 0.2784 1.036 0.972 1.105 3.6 

MIXSEXV 0.1261 0.0133 1.134 1.027 1.254 13.4 

CHCOUNT -0.0915 <.0001 0.913 0.881 0.945 -8.7 

VCOUNT -0.2593 <.0001 0.772 0.733 0.813 -22.8 

MOVEFLAG 0.2149 0.001 1.24 1.091 1.409 24 

POST -0.5775 <.0001 0.561 0.507 0.621 -43.9 

MANATEE 0.3671 <.0001 1.444 1.281 1.627 44.4 

MANAPOST 0.2369 0.0006 1.267 1.107 1.451 26.7 

115

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 3: Pinellas County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.0397 0.5091

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1184 <.0001 1.126 1.114 1.138 12.6 

ABUSE -0.0368 0.2064 0.964 0.91 1.021 -3.6 

NEGLECT 0.0115 0.6835 1.012 0.957 1.069 1.2 

AVGCTAGE -0.00139 0.3104 0.999 0.996 1.001 -0.1 

AVG_VAGE -0.0213 <.0001 0.979 0.974 0.984 -2.1 

ALLWHITEC -0.0569 0.358 0.945 0.837 1.067 -5.5 

MIXRACEC 0.1684 0.0083 1.183 1.044 1.341 18.3 

ALLWHITEV -0.1 0.0951 0.905 0.805 1.018 -9.5 

MIXRACEV -0.3066 0.0125 0.736 0.579 0.936 -26.4 

ALLHISPC 0.0928 0.4336 1.097 0.87 1.384 9.7 

MIXETHC 0.2345 0.0178 1.264 1.041 1.535 26.4 

ALLHISPV -0.1608 0.104 0.851 0.701 1.034 -14.9 

MIXETHV 0.133 0.4465 1.142 0.811 1.609 14.2 

ALLMALEC -0.1372 0.0069 0.872 0.789 0.963 -12.8 

MIXSEXC 0.41 <.0001 1.507 1.435 1.583 50.7 

ALLFEMV 0.0302 0.1994 1.031 0.984 1.079 3.1 

MIXSEXV 0.1106 0.0024 1.117 1.04 1.200 11.7 

CHCOUNT -0.0708 <.0001 0.932 0.908 0.956 -6.8 

VCOUNT -0.1823 <.0001 0.833 0.804 0.864 -16.7 

MOVEFLAG 0.1792 <.0001 1.196 1.099 1.302 19.6 

POST -0.2571 <.0001 0.773 0.742 0.806 -22.7 

116

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 3: Hillsborough County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.2501 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1073 <.0001 1.113 1.103 1.123 11.3 

ABUSE -0.0436 0.1081 0.957 0.908 1.000 -4.3 

NEGLECT 0.053 0.0409 1.054 1.002 1.109 5.4 

AVGCTAGE -0.00205 0.0908 0.998 0.996 1.000 -0.2 

AVG_VAGE -0.00415 0.0732 0.996 0.991 1.000 -0.4 

ALLWHITEC -0.0131 0.7956 0.987 0.894 1.09 -1.3 

MIXRACEC 0.1087 0.0509 1.115 1.000 1.243 11.5 

ALLWHITEV -0.2302 <.0001 0.794 0.721 0.875 -20.6 

MIXRACEV -0.1526 0.1007 0.858 0.716 1.03 -14.2 

ALLHISPC 0.1229 0.0288 1.131 1.013 1.262 13.1 

MIXETHC 0.16 0.0024 1.174 1.058 1.301 17.4 

ALLHISPV -0.0538 0.2836 0.948 0.859 1.046 -5.2 

MIXETHV 0.3029 0.0003 1.354 1.147 1.598 35.4 

ALLMALEC -0.2823 <.0001 0.754 0.686 0.829 -24.6 

MIXSEXC 0.3586 <.0001 1.431 1.369 1.497 43.1 

ALLFEMV 0.0388 0.0823 1.04 0.995 1.086 4 

MIXSEXV 0.0636 0.0509 1.066 1.000 1.136 6.6 

CHCOUNT -0.0183 0.086 0.982 0.962 1.003 -1.8 

VCOUNT -0.1993 <.0001 0.819 0.795 0.845 -18.1 

MOVEFLAG 0.0736 0.0591 1.076 0.997 1.162 7.6 

POST -0.2995 <.0001 0.741 0.714 0.770 -25.9 

117

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 3: Pinellas-Hillsborough Interaction 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.2374 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.1118 <.0001 1.118 1.111 1.126 11.8 

ABUSE -0.043 0.0303 0.958 0.921 0.996 -4.2 

NEGLECT 0.0338 0.0762 1.034 0.996 1.074 3.4 

AVGCTAGE -0.0017 0.0614 0.998 0.997 1.000 -0.2 

AVG_VAGE -0.0125 <.0001 0.988 0.984 0.991 -1.2 

ALLWHITEC -0.0306 0.4335 0.97 0.898 1.047 -3 

MIXRACEC 0.1322 0.0016 1.141 1.051 1.239 14.1 

ALLWHITEV -0.1743 <.0001 0.84 0.78 0.905 -16 

MIXRACEV -0.2046 0.0056 0.815 0.705 0.942 -18.5 

ALLHISPC 0.123 0.0151 1.131 1.024 1.249 13.1 

MIXETHC 0.1703 0.0002 1.186 1.082 1.299 18.6 

ALLHISPV -0.0788 0.0777 0.924 0.847 1.009 -7.6 

MIXETHV 0.2448 0.0013 1.277 1.101 1.482 27.7 

ALLMALEC -0.2104 <.0001 0.81 0.757 0.868 -19 

MIXSEXC 0.3823 <.0001 1.466 1.418 1.515 46.6 

ALLFEMV 0.0341 0.035 1.035 1.002 1.068 3.5 

MIXSEXV 0.0854 0.0004 1.089 1.039 1.142 8.9 

CHCOUNT -0.0373 <.0001 0.963 0.948 0.979 -3.7 

VCOUNT -0.193 <.0001 0.825 0.805 0.844 -17.5 

MOVEFLAG 0.1197 <.0001 1.127 1.065 1.193 12.7 

POST -0.3017 <.0001 0.74 0.712 0.768 -26 

PINELLAS -0.1714 <.0001 0.842 0.811 0.875 -15.8 

PINEPOST 0.0515 0.0693 1.053 0.996 1.113 5.3 

118

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 4: Pasco County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept -0.2055 0.1071

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0821 <.0001 1.086 1.070 1.101 8.6 

ABUSE -0.1157 0.0095 0.891 0.816 0.972 -10.9 

NEGLECT -0.1371 0.0017 0.872 0.800 0.950 -12.8 

AVGCTAGE -0.00217 0.3266 0.998 0.994 1.002 -0.2 

AVG_VAGE -0.00714 0.0721 0.993 0.985 1.001 -0.7 

ALLWHITEC -0.0619 0.6751 0.940 0.704 1.255 -6 

MIXRACEC -0.174 0.2703 0.840 0.617 1.145 -16 

ALLWHITEV -0.252 0.0531 0.777 0.602 1.003 -22.3 

MIXRACEV 0.1332 0.6201 1.142 0.675 1.934 14.2 

ALLHISPC -0.039 0.8059 0.962 0.705 1.313 -3.8 

MIXETHC 0.1432 0.2943 1.154 0.883 1.508 15.4 

ALLHISPV 0.0281 0.8322 1.029 0.793 1.334 2.9 

MIXETHV 0.4896 0.044 1.632 1.013 2.628 63.2 

ALLMALEC -0.1262 0.1451 0.881 0.744 1.045 -11.9 

MIXSEXC 0.5459 <.0001 1.726 1.589 1.876 72.6 

ALLFEMV 0.0295 0.43 1.030 0.957 1.108 3 

MIXSEXV 0.0493 0.3722 1.050 0.943 1.171 5 

CHCOUNT -0.0927 <.0001 0.911 0.873 0.951 -8.9 

VCOUNT -0.1307 <.0001 0.877 0.828 0.93 -12.3 

MOVEFLAG 0.2081 0.003 1.231 1.073 1.413 23.1 

POST -0.1701 <.0001 0.844 0.790 0.900 -15.6 

119

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 4: Lee 2 County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept -0.6691 <.0001

Point

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0581 <.0001 1.060 1.045 1.075 6 

ABUSE 0.0226 0.6258 1.023 0.934 1.120 2.3 

NEGLECT -0.0943 0.0362 0.910 0.833 0.994 -9 

AVGCTAGE 0.00268 0.2305 1.003 0.998 1.007 0.3 

AVG_VAGE -0.0194 <.0001 0.981 0.973 0.989 -1.9 

ALLWHITEC -0.2541 0.0155 0.776 0.631 0.953 -22.4 

MIXRACEC 0.0819 0.4256 1.085 0.887 1.328 8.5 

ALLWHITEV -0.2617 0.0099 0.770 0.631 0.939 -23 

MIXRACEV -0.204 0.268 0.815 0.568 1.170 -18.5 

ALLHISPC 0.2955 0.0065 1.344 1.086 1.663 34.4 

MIXETHC 0.1008 0.3013 1.106 0.914 1.339 10.6 

ALLHISPV -0.0189 0.8481 0.981 0.809 1.191 -1.9 

MIXETHV 0.1735 0.2598 1.189 0.88 1.609 18.9 

ALLMALEC 0.1318 0.149 1.141 0.954 1.365 14.1 

MIXSEXC 0.5163 <.0001 1.676 1.539 1.824 67.6 

ALLFEMV 0.0388 0.3236 1.04 0.962 1.123 4 

MIXSEXV 0.0762 0.1844 1.079 0.964 1.208 7.9 

CHCOUNT -0.0638 0.0014 0.938 0.902 0.976 -6.2 

VCOUNT -0.1349 <.0001 0.874 0.826 0.924 -12.6 

MOVEFLAG 0.2364 0.0018 1.267 1.092 1.469 26.7 

POST -0.5228 <.0001 0.593 0.553 0.636 -40.7 

120

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 4: Pasco-Lee 2 Interaction 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept -0.6497 <.0001

Point

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0704 <.0001 1.073 1.062 1.084 7.3 

ABUSE -0.053 0.0987 0.948 0.891 1.010 -5.2 

NEGLECT -0.118 0.0002 0.889 0.836 0.945 -11.1 

AVGCTAGE 0.000184 0.9068 1.000 0.997 1.003 0 

AVG_VAGE -0.0133 <.0001 0.987 0.981 0.992 -1.3 

ALLWHITEC -0.2057 0.0148 0.814 0.69 0.961 -18.6 

MIXRACEC -0.0345 0.686 0.966 0.817 1.142 -3.4 

ALLWHITEV -0.2671 0.0009 0.766 0.654 0.896 -23.4 

MIXRACEV -0.114 0.4477 0.892 0.665 1.198 -10.8 

ALLHISPC 0.1954 0.0287 1.216 1.021 1.449 21.6 

MIXETHC 0.1122 0.1555 1.119 0.958 1.306 11.9 

ALLHISPV 0.00232 0.9766 1.002 0.858 1.171 0.2 

MIXETHV 0.2338 0.0676 1.263 0.983 1.624 26.3 

ALLMALEC -0.0162 0.7975 0.984 0.869 1.113 -1.6 

MIXSEXC 0.5306 <.0001 1.700 1.602 1.804 70 

ALLFEMV 0.0359 0.185 1.037 0.983 1.093 3.7 

MIXSEXV 0.0687 0.0832 1.071 0.991 1.158 7.1 

CHCOUNT -0.0756 <.0001 0.927 0.901 0.954 -7.3 

VCOUNT -0.1355 <.0001 0.873 0.839 0.909 -12.7 

MOVEFLAG 0.2226 <.0001 1.249 1.129 1.382 24.9 

POST -0.5361 <.0001 0.585 0.546 0.627 -41.5 

PASCO 0.5606 <.0001 1.752 1.649 1.861 75.2 

PASCOPOST 0.3774 <.0001 1.458 1.327 1.602 45.8 

121

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 5: Broward County 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.2429 <.0001

Point

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0663 <.0001 1.069 1.059 1.078 6.9 

ABUSE -0.4736 <.0001 0.623 0.593 0.654 -37.7 

NEGLECT -0.4011 <.0001 0.67 0.638 0.703 -33.0 

AVGCTAGE -0.00064 0.6047 0.999 0.997 1.002 -0.1 

AVG_VAGE -0.0133 <.0001 0.987 0.982 0.991 -1.3 

ALLWHITEC -0.252 <.0001 0.777 0.702 0.861 -22.3 

MIXRACEC -0.1012 0.056 0.904 0.815 1.003 -9.6 

ALLWHITEV -0.0373 0.4636 0.963 0.872 1.065 -3.7 

MIXRACEV -0.1668 0.0775 0.846 0.703 1.019 -15.4 

ALLHISPC 0.0866 0.0868 1.090 0.988 1.204 9.0 

MIXETHC 0.1825 0.0006 1.200 1.082 1.332 20.0 

ALLHISPV -0.0225 0.6283 0.978 0.893 1.071 -2.2 

MIXETHV -0.0235 0.7962 0.977 0.817 1.168 -2.3 

ALLMALEC 0.00976 0.8324 1.010 0.923 1.105 1.0 

MIXSEXC 0.473 <.0001 1.605 1.536 1.677 60.5 

ALLFEMV 0.0497 0.0182 1.051 1.008 1.095 5.1 

MIXSEXV 0.0507 0.1108 1.052 0.988 1.120 5.2 

CHCOUNT -0.0277 0.0196 0.973 0.95 0.996 -2.7 

VCOUNT -0.0983 <.0001 0.906 0.878 0.935 -9.4 

MOVEFLAG 0.1113 0.0088 1.118 1.028 1.215 11.8 

POST -0.1625 <.0001 0.850 0.819 0.882 -15.0 

122

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 5: Palm Beach County 

Maximum Likelihood Estimates Odds Ratio Estimate 

Parameter Estimate Pr > ChiSq 

Intercept 0.2047 0.0007

Point

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0694 <.0001 1.072 1.061 1.083 7.2 

ABUSE -0.5179 <.0001 0.596 0.562 0.631 -40.4 

NEGLECT -0.4582 <.0001 0.632 0.598 0.669 -36.8 

AVGCTAGE -0.00164 0.2395 0.998 0.996 1.001 -0.2 

AVG_VAGE -0.025 <.0001 0.975 0.970 0.980 -2.5 

ALLWHITEC -0.1118 0.064 0.894 0.794 1.007 -10.6 

MIXRACEC 0.0803 0.2073 1.084 0.956 1.228 8.4 

ALLWHITEV -0.0459 0.4392 0.955 0.850 1.073 -4.5 

MIXRACEV -0.0302 0.7846 0.970 0.781 1.205 -3 

ALLHISPC 0.2131 0.0001 1.238 1.111 1.379 23.8 

MIXETHC 0.0482 0.399 1.049 0.938 1.174 4.9 

ALLHISPV -0.0169 0.7432 0.983 0.888 1.088 -1.7 

MIXETHV -0.0873 0.3689 0.916 0.757 1.109 -8.4 

ALLMALEC -0.2504 <.0001 0.778 0.696 0.871 -22.2 

MIXSEXC 0.5044 <.0001 1.656 1.572 1.745 65.6 

ALLFEMV 0.0267 0.2794 1.027 0.979 1.078 2.7 

MIXSEXV 0.1129 0.0021 1.120 1.042 1.203 12 

CHCOUNT -0.0378 0.0014 0.963 0.941 0.985 -3.7 

VCOUNT -0.0921 <.0001 0.912 0.881 0.944 -8.8 

MOVEFLAG 0.115 0.0156 1.122 1.022 1.231 12.2 

POST -0.0685 0.0017 0.934 0.895 0.975 -6.6 

123

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
PAIR 5: Broward-Palm Beach Interaction 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.1762 <.0001

Point

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0673 <.0001 1.07 1.062 1.077 7.0 

ABUSE -0.4898 <.0001 0.613 0.59 0.636 -38.7 

NEGLECT -0.4239 <.0001 0.655 0.631 0.679 -34.5 

AVGCTAGE -0.00095 0.3044 0.999 0.997 1.001 -0.1 

AVG_VAGE -0.0185 <.0001 0.982 0.978 0.985 -1.8 

ALLWHITEC -0.1859 <.0001 0.83 0.769 0.897 -17.0 

MIXRACEC -0.0247 0.5436 0.976 0.901 1.057 -2.4 

ALLWHITEV -0.0473 0.2202 0.954 0.884 1.029 -4.6 

MIXRACEV -0.112 0.1182 0.894 0.777 1.029 -10.6 

ALLHISPC 0.1415 0.0001 1.152 1.071 1.239 15.2 

MIXETHC 0.1197 0.002 1.127 1.045 1.216 12.7 

ALLHISPV -0.0194 0.573 0.981 0.917 1.049 -1.9 

MIXETHV -0.0454 0.4933 0.956 0.839 1.088 -4.4 

ALLHISPV -0.0992 0.0056 0.906 0.844 0.971 -9.4 

MIXSEXC 0.4863 <.0001 1.626 1.573 1.682 62.6 

ALLFEMV 0.042 0.0086 1.043 1.011 1.076 4.3 

MIXSEXV 0.0789 0.001 1.082 1.032 1.134 8.2 

CHCOUNT -0.0336 <.0001 0.967 0.951 0.983 -3.3 

VCOUNT -0.0937 <.0001 0.911 0.890 0.932 -8.90 

MOVEFLAG 0.1133 0.0003 1.120 1.053 1.192 12.00 

POST -0.058 0.0069 0.944 0.905 0.984 -5.60 

BROWARD 0.0776 0.0002 1.081 1.037 1.126 8.10 

BROWPOST -0.1082 0.0001 0.897 0.849 0.949 -10.30

124

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Significance and Shared Significance of Variables 

PAIR 1 PAIR 2 PAIR 3 PAIR 4 PAIR 5

VARIABLE

Man-Lee1 Man-Sar Pin-Hills Pasco-Lee2 Man-Lee2

Allegations # per 

Report <.0001 <.0001 <.0001 <.0001 <.0001

Allegations Abuse 0.0414 0.0009 0.0303 0.0987 <.0001

Allegations Neglect <.0001 0.0017 0.0762 0.0002 <.0001

Caretaker Avg Age 0.8708 0.0314 0.0614 0.9068 0.3044

Victim Avg Age <.0001 0.0006 <.0001 <.0001 <.0001

Caretaker All White 0.0016 0.0555 0.4335 0.0148 <.0001

Caretaker Mixed Race 0.4354 0.2121 0.0016 0.6860 0.5436

Vicitm All White 0.1162 0.8463 <.0001 0.0009 0.2202

Vicitm Mixed Race 0.9638 0.4040 0.0056 0.4477 0.1182

Caretaker All Hispanic 0.0047 0.0358 0.0151 0.0287 0.0001

Caretaker Mixed

Ethnicity 0.0358 0.0040 0.0002 0.1555 0.0020

Victim All Hispanic 0.4306 0.0545 0.0777 0.9766 0.5730

Vicitm Mixed

Ethnicity 0.7071 0.4514 0.0013 0.0676 0.4933

Caretaker All Male 0.7219 0.3082 <.0001 0.7975 0.0056

Caretaker Mixed <.0001 <.0001 <.0001 <.0001 <.0001

Victim All Female 0.5241 0.2784 0.0350 0.1850 0.0086

Vicitm Mixed 0.0297 0.0133 0.0004 0.0832 0.0010

Other

Children

# per Report <.0001 <.0001 <.0001 <.0001 <.0001

Victims # per Report <.0001 <.0001 <.0001 <.0001 <.0001

Family

Move

Moved in 

Post Period <.0001 0.0010 <.0001 <.0001 0.0003

POST PERIOD <.0001 <.0001 <.0001 <.0001 0.0069

EXPERIMENTAL 

COUNTY <.0001 <.0001 <.0001 <.0001 0.0002

INTERACTION <.0001 0.0006 0.0693 <.0001 0.0001

The most interesting of the significant variables shared by all county pairs in the 

model is Caretaker Ethnicity, which plays a significant role in the model for all county 

pairs even in counties where Hispanics are a smaller percentage of the population, e.g. 

Sarasota and Lee. The original variable was individual and dichotomous, coded for 

Hispanic or Non-Hispanic. That variable was converted into a series of three dummy

variables-- All Hispanic, All Non-Hispanic, and Mixed Hispanic/Non-Hispanic – to 

determine ethnicity on a family level. A In a county-by-county breakdown, it seems that 

the significance in each county pair is driven by the significance in the non-Sheriff 

125

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
counties. The odds percentage of substantiating reports with All Hispanic Caretakers is 

not significant in any of the Sheriff counties; however, with the exception of Sarasota, it 

is significant in all of the comparison counties. Mixed ethnicity is also significant in 

most of the county pairs, although in this situation the significance does not seem driven 

by individual counties as much as their combination. 

VARIABLE Manatee Lee1 PAIR 1

Caretaker All Hispanic X X

Caretaker 

Mixed 

Hispanic/Non X

Manatee Sarasota PAIR 2

Caretaker All Hispanic X

Caretaker Mixed Hispanic/Non X X

Pinellas Hills PAIR 2

Caretaker All Hispanic X X

Caretaker Mixed Hispanic/Non X X X

Pasco Lee2 PAIR 4

Caretaker All Hispanic X X

Caretaker Mixed Hispanic/Non

Broward PB PAIR 5

Caretaker All Hispanic X X

Caretaker Mixed Hispanic/Non X X

It is interesting to note that although caretaker ethnicity may not always register 

as significant in individual counties, it may still register as significant in the county pair. 

That this variable is significant at all is surprising because the Hispanic population in five 

of the counties and four of the county pairs is relatively small, although the difference 

between the average percentage of the population that is Hispanic in the Sheriff counties 

(9.08%) and average in non-Sheriff counties (8.84%) is also small.1

 

 1

 http://quickfacts.census.gov 

126

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX C 

Hazard Function Graphs and Statistical Support: 

18 and 24 month Duration 

127

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Number of Families for Recurrence Hazard Function Runs: 18 month duration 

COUNTY 

PAIR COUNTY STAGE TOTAL Recurred Censored* Percent 

Censored

Pre 2200 705 1495 67.95

Manatee Post 7397 3888 3509 47.44

Pre 2900 890 2010 69.31 PAIR 1

Lee 1 Post 11111 6031 5080 45.72

Pre 2200 705 1495 67.95

Manatee Post 7397 3888 3509 47.44

Pre 1729 493 1236 71.49 PAIR 2

Sarasota Post 6493 3445 3048 46.94

Pre 14500 4263 10237 70.6 Pinellas Post 15179 10002 5177 34.11

Pre 17404 4993 12411 71.31 PAIR 3

Hillsborough Post 18111 12250 5861 32.36

Pre 6280 1854 4426 70.48

Pasco Post 6030 4361 1669 27.68

Pre 7171 2094 5077 70.8 PAIR 4

Lee 2 Post 6648 4853 1795 27

Pre 17429 3969 13460 77.23 Broward Post 24392 16579 7813 32.03

Pre 12238 3368 8870 72.48 PAIR 5

Palm Beach Post 17335 12147 5188 29.93

* Includes families with no recurrence over the 18 month duration and families with 

first reports occurring too late in the 18 month duration to allow for recurrence

128

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Number of Families for Recidivism Hazard Function Runs: 18 month duration

COUNTY 

PAIR COUNTY STAGE TOTAL Recurred Censored* Percent 

Censored

Pre 1498 2515 2194 65.75

Manatee Post 4709 513 985 46.59

Pre 1228 421 807 65.72 PAIR 1

Lee 1 Post 3662 2013 1649 45.03

Pre 1498 2515 2194 46.59

Manatee Post 4709 513 985 65.75

Pre 980 312 668 68.16 PAIR 2

Sarasota Post 3125 1824 1301 41.63

Pre 8880 2957 5923 66.7

Pinellas Post 8243 5598 2645 32.09

Pre 11484 3672 7812 68.03 PAIR 3

Hillsborough Post 10651 7345 3306 31.04

Pre 3327 1121 2206 66.31

Pasco Post 2925 2123 802 27.42

Pre 3013 1034 1979 65.68 PAIR 4

Lee 2 Post 1907 1365 542 28.42

Pre 9998 2546 7452 74.53 Broward Post 13659 9442 4217 30.87

Pre 6959 2225 4734 68.03 PAIR 5

Palm Beach Post 9919 7016 2903 29.27

* Includes families with no recurrence over the 18 month duration and families with 

first reports occuring too late in the 18 month duration to allow for recurrence

129

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Number of Families for Recurrence Hazard Function Runs: 24 month duration 

COUNTY 

PAIR COUNTY STAGE TOTAL Recurred Censored* Percent 

Censored 

Manatee Pre 2200 783 1417 64.41 

Post 7397 4665 2732 36.93 

Pre 2900 986 1914 66 PAIR 1 Lee 1 

Post 11111 7172 3939 35.45 

Manatee Pre 2200 783 1417 64.41 

Post 7397 4665 2732 36.93 

Pre 1729 550 1179 68.19 PAIR 2 Sarasota 

Post 6493 4123 2370 36.5 

Pinellas Pre 14500 4865 9635 66.45 

Post 15179 11949 3230 21.28 

Pre 17404 5685 11719 67.34 PAIR 3 Hillsborough 

Post 18111 14529 3582 19.78 

Pasco Pre 6280 2120 4160 66.24 

Post 6030 5298 732 12.14 

Pre 7171 2375 4796 66.88 PAIR 4 Lee 2 

Post 6648 5843 805 12.11 

Broward Pre 17429 4633 12796 73.42 

Post 24392 19938 4454 18.26 

Pre 12238 3882 8356 68.28 PAIR 5 Palm Beach 

Post 17335 14450 2885 16.64 

* Includes families with no recurrence over the 24 month duration and families 

with first reports occurring too late in the 24 month duration to allow for

recurrence 

130

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Number of Families with Substantiated Reports for Recidivism Hazard Function 

Runs: 24 month duration 

COUNTY 

PAIR COUNTY STAGE TOTAL Recurred Censored* Percent 

Censored 

Pre 1498 568 930 62.08 

Manatee Post 4709 3033 1676 35.59 

Pre 1228 465 763 62.13 PAIR 1 

Lee 1 Post 3662 2398 1264 34.52 

Pre 1498 568 930 62.08 

Manatee Post 4709 3033 1676 35.59 

Pre 980 343 637 65 PAIR 2 

Sarasota Post 3125 2118 1007 32.22 

Pre 8880 3358 5522 62.18 Pinellas Post 8243 6633 1610 19.53 

Pre 11484 4161 7323 63.77 PAIR 3 

Hillsborough Post 10651 8689 1962 18.42 

Pre 3327 1279 2048 61.56 

Pasco Post 2925 2599 326 11.15 

Pre 3013 1159 1854 61.53 PAIR 4 

Lee 2 Post 1907 1671 236 12.38 

Pre 9998 2954 7044 70.45 Broward Post 13659 11227 2432 17.81 

Pre 6959 2522 4437 63.76 PAIR 5 

Palm Beach Post 9919 8285 1634 16.47 

* Includes families with no recidivism over the 24 month duration and families with 

first reports occurirng too late in the 24 month duration to allow for recidivism 

131

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Recurrence Hazard Function Statistics: 24 month duration

Log-Rank Test of Equality over Strata

County 

Pair Tested Strata ChiSquare 

DF Pr > ChiSquare 

Sig 

Manatee-Lee 

County and Pre-Post 1064.5544 3 <.0001 X 

County for Pre 1.1361 1 0.2865 

County for Post 3.8884 1 0.0486 X 

Pre-Post for Manatee 398.4084 1 <.0001 X 

PAIR 1 

Pre-Post for Lee 660.8201 1 <.0001 X 

Manatee-Sarasota 

County and Pre-Post 833.0608 3 <.0001 X 

County for Pre 6.8295 1 0.009 X 

County for Post 0.0844 1 0.7714 

Pre-Post for Manatee 398.4084 1 <.0001 X 

PAIR 2 

Pre-Post for Sarasota 435.3567 1 <.0001 X 

Pinellas-Hillsborough 

County and Pre-Post 13365.704 3 <.0001 X 

County for Pre 2.4442 1 0.118 

County for Post 12.8869 1 0.0003 X 

Pre-Post for Pinellas 5695.1916 1 <.0001 X 

PAIR 3 

Pre-Post for Hillsborough 7662.9324 1 <.0001 X 

Pasco-Lee2 

County and Pre-Post 7758.1369 3 <.0001 X 

County for Pre 0.1514 1 0.6972 

County for Post 0.3887 1 0.533 

Pre-Post for Pasco 3638.4116 1 <.0001 X 

PAIR 4 

Pre-Post for Lee2 4116.87 1 <.0001 X 

Broward-Palm Beach 

County and Pre-Post 19040.1487 3 <.0001 X 

County for Pre 98.0469 1 <.0001 X 

County for Post 26.8643 1 <.0001 X 

Pre-Post for Broward 11745.7966 1 <.0001 X 

PAIR 5 

Pre-Post for Palm Beach 7245.109 1 <.0001 X 

132

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Recidivism Hazard Function Statistics: 24 month duration

Log-Rank Test of Equality over Strata

County 

Pair Tested Strata ChiSquare 

DF Pr > ChiSquare 

Sig 

Manatee-Lee 1 

County and Pre-Post 450.0507 3 <.0001 X 

County for Pre 0.06 1 0.8065 

County for Post 0.6825 1 0.4087 

Pre-Post for Manatee 243.8317 1 <.0001 X 

PAIR 1 

Pre-Post for Lee 206.1376 1 <.0001 X 

Manatee-Sarasota 

County and Pre-Post 510.0148 3 <.0001 X 

County for Pre 2.2878 1 0.1304 

County for Post 12.6509 1 0.0004 X 

Pre-Post for Manatee 243.8317 1 <.0001 X 

PAIR 2 

Pre-Post for Sarasota 257.0851 1 <.0001 X 

Pinellas-Hillsborough 

County and Pre-Post 7232.1626 3 <.0001 X 

County for Pre 4.8983 1 0.0269 

County for Post 3.4458 1 0.0634 X 

Pre-Post for Pinellas 2911.8938 1 <.0001 X 

PAIR 3 

Pre-Post for Hillsborough 4320.5186 1 <.0001 X 

Pasco-Lee 2 

County and Pre-Post 2634.0596 3 <.0001 X 

County for Pre 0.1376 1 0.7107 

County for Post 2.6696 1 0.1023 

Pre-Post for Pasco 1549.2658 1 <.0001 X 

PAIR 4 

Pre-Post for Lee2 1063.6623 1 <.0001 X 

Broward-Palm Beach 

County and Pre-Post 9515.2841 3 <.0001 X 

County for Pre 90.6585 1 <.0001 X 

County for Post 8.05 1 0.0046 X 

Pre-Post for Broward 6092.9486 1 <.0001 X 

PAIR 5 

Pre-Post for Palm Beach 3396.4662 1 <.0001 X 

133

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX D 

Survival Estimates for Recurrence and Recidivism 

by County Pair 

134

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
SURVIVAL ESTIMATES FOR RECURRENCE 

PAIR 1: 

Manatee- Lee

PAIR 2: 

Manatee-Sarasota 

 

Pr > ChiSq Hazard 

Ratio 

Estimated

Change 

in Odds 

Pr > ChiSq Hazard 

Ratio 

Estimated

Change 

in Odds 

MALTOTAL 0.2759 1.005 -0.5 0.0093 1.015 -1.5 

ABUSE 0.0166 1.097 -9.7 0.0073 1.131 -13.1 

NEGLECT 0.0421 1.070 -7.0 0.0915 1.072 -7.2

AVGCTAGE 0.9311 1.000 0.0 0.1607 0.997 0.3

AVGVAGE <.0001 0.964 3.6 <.0001 0.961 3.9 

ALLWHITEC 0.8936 0.989 1.1 0.5196 0.941 5.9

MIXRACEC 0.0452 1.178 -17.8 0.4319 1.081 -8.1

ALLWHITEV 0.5251 1.054 -5.4 0.2222 1.118 -11.8

MIXRACEV 0.6266 0.943 5.7 0.4464 1.108 -10.8

ALLHISPC 0.0181 0.771 22.9 0.0346 0.705 29.5 

MIXETHC 0.5108 1.056 -5.6 0.7317 1.047 -4.7

ALLHISPV 0.3982 0.922 7.8 0.0894 0.790 21.0

MIXETHV 0.9342 1.009 -0.9 0.5378 0.910 9.0

ALLMALEC 0.0148 1.178 -17.8 0.0574 1.172 -17.2

MIXSEXC 0.0044 0.912 8.8 <.0001 0.852 14.8 

ALLFEMV 0.7549 1.010 -1.0 0.1376 1.061 -6.1

MIXSEXV 0.5624 1.025 -2.5 0.0755 1.096 -9.6

CHCOUNT 0.0078 1.043 -4.3 0.0138 1.047 -4.7 

VCOUNT 0.0027 1.065 -6.5 0.3475 1.025 -2.5

SBINDXHI 0.0072 0.800 20.0 0.0649 0.838 16.2

SBINDXMD 0.0029 0.776 22.4 0.0091 0.772 22.8 

SBINDXLOW 0.0260 0.824 17.6 0.1723 0.874 12.6

DISPHI 0.9908 0.999 0.1 0.3589 0.949 5.1

DISPMD <.0001 1.318 -31.8 0.0002 1.304 -30.4 

DISPLOW 0.0321 1.070 -7.0 0.0104 1.098 -9.8 

MOVEFLAG <.0001 0.831 16.9 <.0001 0.791 20.9 

SEQ <.0001 1.207 -20.7 <.0001 1.197 -19.7 

PRIORSUB 0.0762 1.149 -14.9 0.2107 1.124 -12.4

135

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
SURVIVAL ESTIMATES FOR RECURRENCE 

PAIR 3: 

Pinellas-Hillsborough 

PAIR 4: 

Pasco-Lee 2 

 

Pr > ChiSq Hazard 

Ratio 

Estimated

Change 

in Odds 

Pr > ChiSq Hazard 

Ratio 

Estimated

Change 

in Odds 

MALTOTAL <.0001 1.019 -1.9 0.0831 1.008 -0.8

ABUSE 0.0052 1.065 -6.5 <.0001 1.176 -17.6 

NEGLECT <.0001 1.095 -9.5 0.0023 1.104 -10.4 

AVGCTAGE 0.3635 0.999 0.1 0.2642 0.998 0.2

AVGVAGE <.0001 0.970 3.0 <.0001 0.965 3.5 

ALLWHITEC 0.4997 0.967 3.3 0.7378 1.033 -3.3

MIXRACEC 0.0077 1.134 -13.4 0.2375 1.106 -10.6

ALLWHITEV 0.0055 1.146 -14.6 0.9580 1.005 -0.5

MIXRACEV 0.3933 1.062 -6.2 0.0952 0.790 21.0

ALLHISPC 0.6669 0.971 2.9 0.1123 0.839 16.1

MIXETHC 0.0155 0.879 12.1 0.5414 1.050 -5.0

ALLHISPV 0.0525 0.891 10.9 0.8559 1.017 -1.7

MIXETHV 0.5105 1.051 -5.1 0.1915 1.162 -16.2

ALLMALEC 0.0071 1.118 -11.8 0.8457 0.987 1.3

MIXSEXC <.0001 0.910 9.0 0.0001 0.886 11.4 

ALLFEMV 0.2200 1.025 -2.5 0.0930 1.053 -5.3

MIXSEXV 0.8540 1.005 -0.5 0.5540 1.024 -2.4

CHCOUNT <.0001 1.053 -5.3 0.2840 1.016 -1.6

VCOUNT 0.0002 1.042 -4.2 <.0001 1.092 -9.2 

SBINDXHI 0.0124 0.891 10.9 0.0299 0.832 16.8 

SBINDXMD 0.0006 0.847 15.3 0.0035 0.773 22.7 

SBINDXLOW 0.0405 0.906 9.4 0.0070 0.786 21.4 

DISPHI <.0001 1.119 -11.9 0.1646 1.072 -7.2

DISPMD <.0001 1.240 -24.0 <.0001 1.238 -23.8 

DISPLOW <.0001 1.118 -11.8 0.0007 1.112 -11.2 

MOVEFLAG <.0001 0.831 16.9 0.0040 0.894 10.6 

SEQ <.0001 1.202 -20.2 <.0001 1.232 -23.2 

PRIORSUB 0.0565 1.090 -9.0 0.2599 1.093 -9.3

136

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
SURVIVAL ESTIMATES FOR RECURRENCE 

PAIR 5: 

Broward-Palm Beach 

 

Pr > ChiSq Hazard 

Ratio 

Estimated

Change 

in Odds 

MALTOTAL <.0001 1.018 -1.8 

ABUSE <.0001 1.149 -14.9 

NEGLECT <.0001 1.118 -11.8 

AVGCTAGE 0.0967 0.998 0.2 

AVGVAGE <.0001 0.972 2.8 

ALLWHITEC 0.2344 1.065 -6.5 

MIXRACEC 0.2418 1.061 -6.1 

ALLWHITEV 0.2986 1.056 -5.6 

MIXRACEV 0.5482 0.951 4.9 

ALLHISPC 0.8767 0.992 0.8 

MIXETHC 0.4072 1.040 -4 

ALLHISPV <.0001 0.819 18.1 

MIXETHV 0.7329 1.022 -2.2 

ALLMALEC 0.0006 1.175 -17.5 

MIXSEXC 0.0050 0.944 5.6 

ALLFEMV 0.8180 0.995 0.5 

MIXSEXV 0.7689 0.992 0.8 

CHCOUNT <.0001 1.055 -5.5 

VCOUNT 0.0004 1.043 -4.3 

SBINDXHI 0.1145 0.919 8.1 

SBINDXMD 0.0151 0.875 12.5 

SBINDXLOW 0.7378 1.018 -1.8 

DISPHI 0.8168 0.993 0.7 

DISPMD 0.0014 1.131 -13.1 

DISPLOW 0.5822 1.011 -1.1 

MOVEFLAG <.0001 0.860 14 

SEQ <.0001 1.244 -24.4 

PRIORSUB 0.3115 1.053 -5.3 

137

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
SURVIVAL ESTIMATES FOR RECIDIVISM 

PAIR 1: 

Manatee- Lee

PAIR 2: 

Manatee-Sarasota 

Pr > ChiSq Hazard 

Ratio 

% 

Change 

in Odds Pr > ChiSq Hazard 

Ratio 

% 

Change 

in Odds 

MALTOTAL 0.1948 1.012 -1.2 0.0075 1.022 -2.2 

ABUSE 0.179 1.128 -12.8 0.4373 1.070 -7.0

NEGLECT 0.2391 1.100 -10.0 0.9672 0.997 0.3

AVGCTAGE 0.9724 1.000 0.0 0.4795 0.997 0.3

AVGVAGE <.0001 0.961 3.9 <.0001 0.955 4.5 

ALLWHITEC 0.9773 1.005 -0.5 0.2873 0.827 17.3

MIXRACEC 0.2186 1.227 -22.7 0.7859 1.048 -4.8

ALLWHITEV 0.3022 1.199 -19.9 0.1053 1.323 -32.3

MIXRACEV 0.6193 1.128 -12.8 0.6345 1.113 -11.3

ALLHISPC 0.5237 0.841 15.9 0.2179 0.691 30.9

MIXETHC 0.1378 1.309 -30.9 0.9098 1.024 -2.4

ALLHISPV 0.2102 0.755 24.5 0.0389 0.612 38.8 

MIXETHV 0.3515 0.809 19.1 0.4578 0.827 17.3

ALLMALEC 0.282 1.205 -20.5 0.9270 1.016 -1.6

MIXSEXC 0.0218 0.832 16.8 0.0171 0.837 16.3 

ALLFEMV 0.0673 0.864 13.6 0.7719 0.978 2.2

MIXSEXV 0.8216 1.022 -2.2 0.9893 0.999 0.1

CHCOUNT 0.043 1.075 -7.5 0.0742 1.068 -6.8 

VCOUNT 0.1707 1.057 -5.7 0.2317 1.053 -5.3

SBINDXHI 0.6306 0.937 6.3 0.6457 0.934 6.6

SBINDXMD 0.4635 0.902 9.8 0.2716 0.841 15.9

SBINDXLOW 0.6849 0.945 5.5 0.7408 0.951 4.9

DISPHI 0.4607 0.928 7.2 0.3056 0.904 9.6

DISPMD <.0001 1.479 -47.9 0.0049 1.364 -36.4 

DISPLOW 0.0969 1.137 -13.7 0.1405 1.117 -11.7

MOVEFLAG 0.0594 0.853 14.7 0.3924 0.933 6.7

SEQ <.0001 1.323 -32.3 <.0001 1.294 -29.4 

138

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
S

 

P

P

PA

Pa

URVIVAL ESTIMATES FOR RECIDIVISM 

AIR 3: 

inellas-Hillsborough 

IR 4: 

sco-Lee 2 

Pr > ChiSq Hazard 

Ratio 

%

C

in

hange 

Odds Pr > ChiSq Hazard 

Ratio 

% 

Ch

n O

ange 

i dds

MALTOTAL <.0001 1.023 -2.3 0.0229 1.023 -2.3

ABUSE 0.6752 1.018 -1.8 0.0413 1.220 -22.0

NEGLECT <.0001 1.178 -17.8 0.0137 1.244 -24.4

AVGCTAGE 0.3413 0.998 0.2 0.9576 1.000 0.0 

AVGVAGE <.0001 0.973 2.7 <.0001 0.961 3.9 

ALLWHITEC 0.2131 1.122 -12.2 0.5983 1.157 -15.7

MIXRACEC 0.0745 1.160 -16.0 0.5183 1.186 -18.6

ALLWHITEV 0.2218 1.117 -11.7 0.9839 0.995 0.5 

MIXRACEV 0.5621 1.077 -7.7 0.1490 0.467 53.3 

ALLHISPC 0.1381 0.825 17.5 0.4323 1.269 -26.9

MIXETHC 0.0081 0.782 21.8 0.4042 1.208 -20.8

ALLHISPV 0.2991 0.889 11.1 0.5383 0.849 15.1 

MIXETHV 0.7071 1.047 -4.7 0.3993 0.759 24.1 

ALLMALEC 0.5735 1.056 -5.6 0.5881 0.903 9.7 

MIXSEXC 0.0195 0.921 7.9 0.0203 0.811 18.9

ALLFEMV 0.0839 1.066 -6.6 0.6166 0.960 4.0 

MIXSEXV 0.0126 1.118 -11.8 0.7736 1.029 -2.9 

CHCOUNT <.0001 1.075 -7.5 0.7472 1.015 -1.5 

VCOUNT 0.0375 1.038 -3.8 0.7516 1.016 -1.6 

SBINDXHI 0.1813 0.918 8.2 0.0921 0.796 20.4 

SBINDXMD 0.4590 0.953 4.7 0.0322 0.735 26.5

SBINDXLOW 0.6927 0.974 2.6 0.0474 0.757 24.3 

DISPHI 0.0267 1.107 -10.7 0.8682 0.981 1.9 

DISPMD 0.0011 1.212 -21.2 0.0100 1.298 -29.8 

DISPLOW 0.0184 1.087 -8.7 0.0024 1.282 -28.2 

MOVEFLAG 0.0002 0.860 14.0 0.2829 0.901 9.9 

SEQ <.0001 1.274 -27.4 <.0001 1.365 -36.5 

139

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
S

P

B

URVIVAL ESTIMATES FOR RECIDIVISM 

AIR 5: 

roward-Palm Beach 

Pr > ChiSq Hazard 

Ratio 

%

C

in

hange 

Odds

MALTOTAL <.0001 1.027 -2.7

ABUSE 0.0370 1.107 -10.7

NEGLECT 0.1313 1.069 -6.9

AVGCTAGE 0.6884 1.001 -0.1

AVGVAGE <.0001 0.972 2.8

ALLWHITEC 0.1257 1.167 -16.7

MIXRACEC 0.0375 1.201 -20.1

ALLWHITEV 0.8972 1.013 -1.3

MIXRACEV 0.9535 0.991 0.9

ALLHISPC 0.6936 0.961 3.9

MIXETHC 0.2166 1.115 -11.5

ALLHISPV 0.0014 0.740 26

MIXETHV 0.4612 0.909 9.1

ALLMALEC 0.0355 1.238 -23.8

MIXSEXC 0.0170 0.903 9.7

ALLFEMV 0.5911 1.024 -2.4

MIXSEXV 0.1755 1.075 -7.5

CHCOUNT 0.0011 1.062 -6.2

VCOUNT 0.0504 1.040 -4

SBINDXHI 0.0111 0.830 17

SBINDXMD 0.0032 0.804 19.6

SBINDXLOW 0.4538 0.947 5.3

DISPHI 0.9712 1.002 -0.2

DISPMD 0.0064 1.183 -18.3

DISPLOW 0.6671 1.018 -1.8

MOVEFLAG 0.0349 0.903 9.7

SEQ <.0001 1.294 -29.4

140

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX E 

Estimated Survival Probabilities for Recurrence and Recidivism: 

Median Lifetime Duration in Days 

141

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
Survival

Probability

Event: New Report 

(Recurrence) 

Event: New Substantiated 

Report (Recidivism) 

 Pre Post Pre Post

Broward 

0.75 172-173 294-295 213-214 433-435

0.50 362-263 839-841 460-461 1279-1305

Palm Beach 

0.75 135-136 289-290 143-144 378-379

0.50 294-295 788-792 327-328 1106-1131

Manatee 

0.75 92-93 251-252 118-119 312-313

0.50 181-182 636-637 236-244 816-833

Lee 

0.75 62-62 233-234 62-63 343-344

0.50 149-150 608-609 175-176 835-976

Sarasota 

0.75 90-92 238-239 92-93 336-338

0.50 179-182 609-611 190-193 835-875

Pasco 

0.75 135-136 398-399 151-153 564-571

0.50 306-307 994-996 383-387 1383-1394

Lee2 

0.75 111-112 362-363 135-138 590-648

0.50 277-278 885-889 391-393

976 days for lowest

S=.65 

Pinellas 

0.75 439-441 832-834 137-138 428-429

0.50 990-996 1637-1640 302-303 1200-1217

Hillsborough 

0.75 430-431 794-795 148-149 396-397

0.50 930-936 1639-1645 325-326 1045-1050

142

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
APPENDIX F 

Statistical Support for Sheriff vs Non-Sheriff 

143

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
ODDS RATIO ESTIMATES FOR SUBSTANTIATION: Sheriff Counties 

 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.1699 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0913 <.0001 1.096 1.089 1.102 9.6 

ABUSE -0.2533 <.0001 0.776 0.752 0.802 -22.4 

NEGLECT -0.2061 <.0001 0.814 0.788 0.84 -18.6 

AVGCTAGE -0.00187 0.0191 0.998 0.997 1.000 -0.2 

AVG_VAGE -0.0145 <.0001 0.986 0.983 0.988 -1.4 

ALLWHITEC -0.2024 <.0001 0.817 0.762 0.876 -18.3 

MIXRACEC -0.0145 0.6936 0.986 0.917 1.059 -1.4 

ALLWHITEV -0.0684 0.0485 0.934 0.873 1.000 -6.6 

MIXRACEV -0.1281 0.0575 0.88 0.771 1.004 -12 

ALLHISPC 0.0968 0.0212 1.102 1.015 1.196 10.2 

MIXETHC 0.2006 <.0001 1.222 1.127 1.325 22.2 

ALLHISPV -0.0395 0.2932 0.961 0.893 1.035 -3.9 

MIXETHV 0.0691 0.3311 1.072 0.932 1.232 7.2 

ALLMALEC -0.0571 0.0554 0.944 0.891 1.001 -5.6 

MIXSEXC 0.4601 <.0001 1.584 1.539 1.631 58.4 

ALLFEMV 0.0289 0.0349 1.029 1.002 1.057 2.9 

MIXSEXV 0.0739 0.0004 1.077 1.034 1.121 7.7 

CHCOUNT -0.0576 <.0001 0.944 0.930 0.958 -5.6 

VCOUNT -0.1426 <.0001 0.867 0.849 0.885 -13.3 

MOVEFLAG 0.158 <.0001 1.171 1.112 1.233 17.1 

POST -0.1532 <.0001 0.858 0.838 0.879 -14.2 

144

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
ODDS RATIO ESTIMATES FOR SUBSTANTIATION: Non-Sheriff Counties 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.1074 0.0019

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0837 <.0001 1.087 1.081 1.093 8.7 

ABUSE -0.2059 <.0001 0.814 0.787 0.842 -18.6 

NEGLECT -0.157 <.0001 0.855 0.828 0.883 -14.5 

AVGCTAGE -0.00108 0.1726 0.999 0.997 1.000 -0.1 

AVG_VAGE -0.0135 <.0001 0.987 0.984 0.99 -1.3 

ALLWHITEC -0.1315 0.0002 0.877 0.819 0.938 -12.3 

MIXRACEC 0.0913 0.0133 1.096 1.019 1.178 9.6 

ALLWHITEV -0.1774 <.0001 0.837 0.783 0.895 -16.3 

MIXRACEV -0.0808 0.1991 0.922 0.815 1.043 -7.8 

ALLHISPC 0.2008 <.0001 1.222 1.140 1.311 22.2 

MIXETHC 0.1627 <.0001 1.177 1.100 1.259 17.7 

ALLHISPV -0.0371 0.2557 0.964 0.904 1.027 -3.6 

MIXETHV 0.1513 0.0072 1.163 1.042 1.299 16.3 

ALLMALEC -0.2065 <.0001 0.813 0.764 0.867 -18.7 

MIXSEXC 0.4253 <.0001 1.53 1.486 1.576 53 

ALLFEMV 0.0342 0.0165 1.035 1.006 1.064 3.5 

MIXSEXV 0.1003 <.0001 1.105 1.061 1.152 10.5 

CHCOUNT -0.0454 <.0001 0.956 0.943 0.969 -4.4 

VCOUNT -0.15 <.0001 0.861 0.844 0.878 -13.9 

MOVEFLAG 0.1413 <.0001 1.152 1.093 1.213 15.2 

POST -0.2188 <.0001 0.804 0.784 0.823 -19.6 

145

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
ODDS RATIO ESTIMATES FOR SUBSTANTIATION: Post * Sheriff Interaction 

Maximum Likelihood Estimates Odds Ratio Estimates 

Parameter Estimate Pr > ChiSq 

Intercept 0.1064 <.0001

Point 

Estimate 

95% Wald

Confidence 

Limits 

Odds 

(percentage) 

MALTOTAL 0.0875 <.0001 1.091 1.087 1.096 9.1 

ABUSE -0.231 <.0001 0.794 0.776 0.812 -20.6 

NEGLECT -0.1821 <.0001 0.834 0.815 0.852 -16.6 

AVGCTAGE -0.00145 0.0098 0.999 0.997 1.000 -0.1 

AVG_VAGE -0.0141 <.0001 0.986 0.984 0.988 -1.4 

ALLWHITEC -0.1664 <.0001 0.847 0.807 0.889 -15.3 

MIXRACEC 0.0383 0.1421 1.039 0.987 1.094 3.9 

ALLWHITEV -0.1226 <.0001 0.885 0.844 0.928 -11.5 

MIXRACEV -0.099 0.0314 0.906 0.828 0.991 -9.4 

ALLHISPC 0.1591 <.0001 1.172 1.112 1.237 17.2 

MIXETHC 0.1776 <.0001 1.194 1.134 1.258 19.4 

ALLHISPV -0.0386 0.1176 0.962 0.917 1.010 -3.8 

MIXETHV 0.1163 0.0083 1.123 1.030 1.225 12.3 

ALLMALEC -0.1263 <.0001 0.881 0.844 0.920 -11.9 

MIXSEXC 0.4431 <.0001 1.558 1.526 1.59 55.8 

ALLFEMV 0.0318 0.0013 1.032 1.013 1.052 3.2 

MIXSEXV 0.0877 <.0001 1.092 1.061 1.124 9.2 

CHCOUNT -0.0498 <.0001 0.951 0.942 0.961 -4.9 

VCOUNT -0.1466 <.0001 0.864 0.851 0.876 -13.6 

MOVEFLAG 0.1496 <.0001 1.161 1.120 1.205 16.1 

POST -0.2232 <.0001 0.8 0.781 0.820 -20 

SHRFCNTY 0.0633 <.0001 1.065 1.040 1.091 6.5 

SHRFPOST 0.0746 <.0001 1.077 1.042 1.114 7.7 

146

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.