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

Department of Justice and prepared the following final report: 

Document Title: Assessing the Offending Activity of Criminal 

Domestic Violence Suspects: Offense 

Specialization, Escalation, and De-Escalation 

Evidence from the Spouse Assault Replication 

Program 

Author(s): Alex R. Piquero, Robert Brame, Jeffrey Fagan, 

Terrie E. Moffitt 

Document No.: 212298 

Date Received: December 2005 

Award Number: 2004-IJ-CX-0013 

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. 
 

Assessing the Offending Activity of Criminal Domestic Violence Suspects: 

Offense Specialization, Escalation, and De-Escalation Evidence from 

the Spouse Assault Replication Program 

Alex R. Piquero 

University of Florida 

Robert Brame 

University of South Carolina 

Jeffrey Fagan 

Columbia University 

Terrie E. Moffitt 

University of Wisconsin & Institute of Psychiatry, Kings College London 

FINAL REPORT SUBMITTED TO NATIONAL INSTITUTE OF JUSTICE 

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. 
2

Table of Contents 

Section Page 

Proposal Abstract 3 

Introduction 4 

Theoretical Context 7 

Specialization in Domestic Violence 9 

Escalation and De-Escalation in Criminal Domestic Violence 11 

Current Study 13 

Data 14 

Analytic Plan 18 

Specialization Analysis Results 26 

-Charlotte Analysis 26 

-Colorado Springs Analysis 27 

-Milwaukee Analysis 29 

-Omaha Analysis 30 

Summary of Specialization Analysis Results 31 

Escalation and De-Escalation Analysis Results 32 

-Charlotte Analysis 32 

-Miami-Dade Analysis 36 

-Milwaukee Analysis 39 

-Omaha Analysis 41 

Summary of Escalation and De-Escalation Analysis Results 43 

Discussion 44 

References 50 

List of Tables 54 

List of Figures 55 

Tables (1-3) 56 

Figures (1-14) 59 

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. 
PROPOSAL ABSTRACT 

Research Goals and Objectives: 

 Two key dimensions of the criminal career paradigm include specialization and 

escalation. Although these topics have generated theoretical and empirical debate in the 

criminal careers area, this line of research has not been integrated into the study of 

domestic violence, and remains limited in several ways. In this project, we build upon 

these limitations and explore, using both official records and victim interviews, issues 

related to specialization and escalation using data from the Spouse Abuse Replication 

Program (SARP). Specifically, we examine (1) the extent to which offenders 

participating in the SARP exhibit a specialized proclivity to violence; and (2) tendencies 

of these individuals to escalate or de-escalate the severity of their attacks against the same 

victim. 

Results 

 First, regarding the extent to which criminal domestic violence offenders 

specialize in violent offending, our analysis reveals that the majority of domestic violence 

offenders with prior official criminal records have been involved in non-violent forms of 

criminal behavior in addition to domestic violence. Second, regarding the question of 

whether the severity of an offender's attacks against the same victim increase, decrease, 

or stay about the same over the course of a well-defined follow-up period, our analysis 

identifies groups of escalators and de-escalators as well as individuals who engage in 

stable low-level aggression and stable high-level aggression. Future research directions 

are identified. 

Keywords: intimate partner violence; criminal careers; specialization; escalation. 

3

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

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4

 

Introduction 

 After a long period of neglect, intimate partner violence has become an 

increasingly prominent research and policy topic over the past twenty-five years (Fagan 

and Browne, 1994:116; Chalk and King, 1998; Dobash and Dobash, 1992; Koss et al., 

1994).1

 National surveys estimate that an act of physical violence is committed by a 

family member in nearly half of all homes during an average 12-month period in the 

United States (Gelles and Straus, 1988). Minimum estimates from these surveys indicate 

that acts of physical aggression between spouses occur in one of six homes each year 

(Fagan and Browne, 1994). Two other recent large-scale surveys also provide a glimpse 

of the problem of intimate partner violence. For example, data from the National Crime 

Victimization Survey (NCVS) indicate that the number of female victims of intimate 

violence declined from 1993 to 1998 (Rennison, 2000). The National Violence Against 

Women Survey (Tjaden and Thoennes, 2000), based on a telephone survey of a 

representative sample of 8,000 U.S. men and 8,000 U.S. women, surveyed individuals 

about their experiences as victims of various forms of violence, including intimate 

partner violence. Amidst the many important findings, three in particular stand out for 

present purposes. First, intimate partner violence is pervasive. Twenty-five (25%) 

percent of the women and 7.6% of men said they were raped and/or physically assaulted 

by a current or former spouse, cohabitating partner, or date at some point in their lifetime. Second, violence against women by intimates is often accompanied by emotionally 

1

We follow Fagan and Browne (1994:119) and consider domestic violence generally, but use the label 

‘intimate partner violence’ throughout to include “the terms wife assault, marital violence, spouse abuse, 

and spouse assault.” 

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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. 
abusive and controlling behavior. Third, females more than males, experience chronic 

and injurious physical assault at the hands of intimate partners. 

 Although considerable effort has been devoted to research on intimate partner 

violence in recent years, knowledge about the criminal careers of domestic violence 

offenders remains limited largely because researchers interested in partner and domestic 

violence have tended to operate under the assumption that partner/domestic batterers 

specialize in that particular offense to the neglect of all others, and that many batterers 

escalate in their offending activity from less to more serious crimes. Until recently, these 

issues have remained virtually unexplored because of the “bifurcation between the fields 

of domestic violence research and criminology” (Moffitt et al., 2000:201; Fagan and 

Browne, 1994). 

A criminal career refers to an individual's crime commission experiences arrayed 

over the life span (Blumstein, Cohen, Roth, and Visher, 1986). A great deal of research 

on criminal careers has emphasized distinctions between those who become involved in 

criminal offending in comparison to those who do not and the frequency of crimes and 

the duration of the criminal career among those who offend (Piquero, Farrington, and 

Blumstein, 2003). Researchers have also asked whether offenders exhibit generalized or 

specialized careers and whether the seriousness of offenses in those careers progresses in 

an orderly fashion (Elliott, 1994; Le Blanc and Fréchette, 1989). The preponderance of 

studies show that offending behavior tends to be a generalized enterprise with relatively 

limited evidence of offense specialization (Piquero et al., 2003). Evidence on the 

escalation and de-escalation of offense seriousness over the course of offending careers is 

less abundant but suggests that escalation tendencies are most pronounced for juvenile 

5

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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. 
6

offenders and de-escalation tendencies are more pronounced for adult offenders 

(Blumstein et al., 1988; Rojek and Erickson, 1982). 

While research on the prevalence and frequency of intimate partner violence and 

victimization has evolved considerably over the past two decades, little progress has been 

made in understanding other features of the criminal careers of domestic violence 

offenders such as the mix of offenses in which they are involved and the progression of 

offense seriousness against the people they victimize. Limited research indicates that 

partner abusers do not specialize but engage in violence against non-partners as well as a 

variety of nonviolent crimes (Fagan and Wexler, 1987), and that careers in marital and 

stranger violence tend to converge as violence in either domain becomes more frequent 

and serious (Fagan and Browne, 1994:253). 

There have been few efforts to integrate the empirical literature on aggression 

within families with other perspectives on violence, and to the extent that there is 

significant overlap, the establishment of linkages between intimate partner violence and 

criminal behavior more generally remains a “critical gap” (Fagan and Browne, 

1994:253). Moreover, since most theory and research into partner abuse has remained 

separate from theory and research into crime, attention from questions about associations 

between partner abuse and crime have been diverted (Moffitt et al., 2000). 

In this report, we integrate the study of the criminal career dimensions of 

specialization and escalation into the study of domestic violence. Specifically, we 

address this gap by using data on the offending activities of spouse assault suspects 

participating in several of the Spouse Assault Replication Program (SARP) sites to better 

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. 
document: (1) the extent to which these individuals exhibit a specialized proclivity to 

violence; and (2) tendencies of these individuals to escalate or de-escalate the severity of 

their attacks against the same victim.2

 Unlike other criminal career/domestic violence 

studies, an important feature of our analysis is that it integrates data from two distinct 

reporting sources, i.e., official records and self-report interviews. 

THEORETICAL CONTEXT 

The extent to which there is a common explanation of crime that applies to all 

offenders is a contentious issue. Gottfredson and Hirschi (1990) argue that all criminal, 

deviant, and analogous acts can be attributed to variations in self-control and available 

opportunities. Their theory advocates a general/static viewpoint of criminal behavior 

which presumes that there is a general cause of crime for all offenders and that, once the 

causal process has played out, change is unlikely. Sampson and Laub (1993) offer an 

important variation to this ‘common explanation’ theory. To these scholars, crime can be 

understood as the product of informal social controls such as the family, school, 

marriage, employment and so on. This approach, characterized as a general/dynamic 

viewpoint, attributes importance to change. 

 Although both sets of scholars agree on the generality assumption, 

developmentalists relax the assumption (of one trajectory for all offenders) thereby 

adding further complexity. Developmentalists are friendly to the notion that both 

persistent individual differences and changing life circumstances are related to 

involvement in crime, and that these factors affect different groups of offenders in 

2

 The escalation portion of this study is not about switching partners or about switching from domestic 

partners to strangers, or continuity of domestic violence across different partners. Instead, it is about 

 

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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. 

7
different ways. The developmental view grants that there are different kinds of 

offenders, each possessing a unique sequelae to crime, as well as a different criminal 

repertoire. As such, developmentalists contend that treating all offenders as emanating 

from the same population would be inconsistent with research documenting offender 

heterogeneity (D’Unger et al., 1998; Nagin and Land, 1993). 

escalation/de-escalation within domestic violence. 

Although several developmental theories exist, one prominent example is 

Moffitt’s (1993) developmental taxonomy. She rejects the assumption that there is a 

general theory of crime and argues for the existence of two distinct groups of offenders. 

One of these offender groups, life-course-persistent, is characterized by continuity in 

offending, and the other group, adolescence-limited, is characterized by change in 

offending. Life-course-persistent offenders originate as a result of the interaction 

between neuropsychological deficits and deficient familial and neighborhood 

environments. These individuals are typically born into families who are ill-prepared to 

perform effective socialization. As a result of ineffective socialization, life-coursepersisters fail in their family life, their school work, and all sorts of interpersonal 

relationships. Since they never learn to control their antisocial proclivities, they act 

impulsively as children, adolescents, and adults. For this group of offenders, continuity 

is the modal behavior, and change is unlikely. The criminal repertoire of life-coursepersisters is believed to include all sorts of criminal acts, including violence. On the 

other hand, adolescence-limited offenders begin offending in adolescence as a function of 

the perceived maturity gap and the peer social context of adolescence. Since 

adolescence-limiteds do not suffer from life-course-persistent type risk factors, as 

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. 
adulthood ensues they are likely to embrace their prosocial tendencies and skills and 

desist. For this group, change is modal. The criminal repertoire of adolescence-limiteds 

is believed to include mainly status and nonviolent delinquent acts. 

 The debate between developmental and general theories hinges on differences, if 

any, between individuals in their patterns of offending and in the covariates that reflect 

possible underlying causal forces (McDermott and Nagin, 2001). Related to this debate 

is the extent to which offenders specialize in offending. Interestingly, the theoretical 

models discussed above make markedly different predictions regarding specialization. 

For both Gottfredson and Hirschi and Sampson and Laub, versatility in offending is the 

norm; in other words, both of these general theories claim that offenders rarely (if ever) 

specialize. For example, Gottfredson and Hirschi (1990:91) contend that “within the 

domain of crime...there will be much versatility among offenders in the criminal acts in 

which they engage.” Similarly, Sampson and Laub (1993:56) contend that “[because of] 

the low level of specialization in specific crimes committed by the Glueck men...[our] 

theoretical framework does not make crime-specific predictions.” Recently, Laub and 

Sampson (2001:63) noted that their “life history narratives [suggest] no major differences 

in the process of desistance for non-violent and violent juvenile offenders.” However, 

developmentalists anticipate both specialized and generalized patterns of criminal 

activity. In Moffitt’s scheme, life-course-persisters engage in both nonviolent and violent 

crimes, while adolescence-limiteds concentrate their crime in the nonviolent domain. 

Specialization in Criminal Domestic Violence 

 Despite evidence suggesting that criminal violence frequently occurs between 

9

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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. 
10

family members as well as between acquaintances and strangers (Bureau of Justice 

Statistics, 2002: Table 34), researchers continue to study these patterns separately leaving 

many important questions unanswered. For example, is family violence a part of a 

generalized pattern of violence? If so, can we expect its career parameters and phases to 

parallel other types of violence patterns (Fagan and Browne, 1994:250)? Is a special 

theory needed to account for partner violence? For example, some scholars believe that 

intimate violence requires its own specific theory (Gelles and Straus, 1979). Or are 

domestic batterers also generalists in that they engage in more general forms of violence, 

as well as different types of non-violent criminal activity (Farrington, 1991; Gottfredson 

and Hirschi, 1990; Piquero, 2000)? 

 Although some research has examined the intersection of family and stranger 

violence (Shields et al., 1988; Fagan et al., 1983), only one study has attempted to 

rigorously examine this issue. Using data from the Dunedin Multidisciplinary Health and 

Development Study, a longitudinal investigation of the health, development, and 

behavior of a cohort of consecutive births (n=1,037) between April 1, 1972 and March 

31, 1973 in Dunedin, New Zealand, Moffitt et al. (2000) used Confirmatory Factor 

Analysis to study the relation between partner abuse and general crime. Three key 

findings emanate from their study. First, partner abuse and general crime represented 

different constructs that were moderately related. Second, group comparisons showed 

that many, but not all, partner abusers also engaged in violence against nonintimates. 

Third, personality analyses showed that partner abuse and general crime shared a strong 

propensity from a trait called negative emotionality. 

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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. 
 In sum, there are too few studies on the specialization of domestic violence 

offenders to draw any firm conclusions. 

Escalation and De-Escalation in Criminal Domestic Violence 

 There is some evidence that criminal careers in intimate partner violence follow 

patterns similar to criminal careers in stranger violence or property crime, with 

discernible patterns of initiation, escalation, continuity, and desistance (Fagan and 

Browne, 1994:151). Herein, we focus on escalation, or “the tendency for offenders to 

move to more serious offense types as offending continues” (Blumstein et al., 1986:84) 

and its conceptual counterweight, de-escalation. 

 Only a handful of studies have examined the nature of escalation within intimate 

partner violence. Using data gathered primarily from samples of female victims of 

intimate partner (marital) violence, some research indicates that such violence escalates 

in frequency and severity over time (Walker, 1984; Pagelow, 1994; Fagan et al., 1984). 

Feld and Straus (1989) used panel data from the 1985 National Family Violence Survey 

and a second wave collected in 1986 to examine patterns of continuity and discontinuity 

in family violence. They found that such patterns varied by the severity of violence in 

the first wave. Although more than half of the sample continued their participation in 

severe violence, ten percent reduced the severity of their violence, and thirty-three 

percent reported no violence during the second year; however, minor assaults in 1985 

were associated with more serious assaults over the second year, suggesting patterns of 

escalation. 

In addition, Johnson (1995:286) argues that it may be misleading to discuss 

11

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12

patterns of escalation in domestic violence for the population as a whole. For families 

experiencing what Johnson refers to as “common couple violence” there is apparently 

very little evidence of escalation. On the other hand, victims of more serious and 

persistent violence—what Johnson (1995) calls “patriarchal terrorism”—apparently 

experience the brunt of the escalation problem. This research suggests that patterns of 

escalation may differ in important ways across the population. Johnson’s exploratory 

research in this area implies that it may be necessary to disaggregate patterns of offense 

mix and escalation. 

In sum, the conclusion drawn from this research seems to support varied career 

trajectories of escalation in intimate partner violence, with some research indicating that 

intimate partner violence may be episodic, with lengthy intervals of nonviolence 

interrupted by shorter periods of intensive violence (Walker, 1984; Fagan, 1989). At the 

same time, several limitations to these prior escalation studies prohibit firm conclusions 

on the extent to which intimate partner violence escalates over time. First, most of these 

studies have not examined the extent to which misdemeanor domestic violence escalates 

over time within the same dyad. Second, prior research has tended to employ outcome 

data from one source; that is, researchers have employed either official records or victim 

self-reports. By employing data from both official records and victim interviews, our 

estimates of criminal career patterns during the follow-up period will not be subject to 

biases arising from suspect interviews and/or drop-out. Third, prior efforts have not 

established a methodological approach, one that can be employed and compared across 

studies, that allows researchers to characterize escalation in a statistical fashion. Finally, 

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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. 
the issue of escalation has yet to be addressed with data from the SARP within the 

methodological context within which we operate. 

Current Study 

 In this study, we build upon prior research and follow Fagan and Browne’s 

(1994:253) suggestion that researchers integrate issues related to both family violence 

and criminal careers. Specifically, using data from the SARP we examine: (1) the extent 

to which offenders exhibit a specialized proclivity toward violence (e.g., specialization), 

and (2) the extent to which attack severity escalates, de-escalates, or stays about the same 

over time (e.g., escalation). In particular, we believe it is useful to document the mix of 

offenses that occur within intimate relationships and to investigate whether offenders will 

exhibit escalation or de-escalation in the seriousness of their offenses against the same 

victim. Distinctions among escalators and non-escalators may prove useful in guiding 

development of theoretical models designed to account for domestic violence (Fagan and 

Browne, 1994). The larger issue is that there may be heterogeneity among domestic 

batterers such that a typology of domestic batterers is relevant (Holtzworth-Munroe et al., 

2000) and an investigation into the kinds of characteristics that help un-pack the 

heterogeneity within domestic batterers will advance knowledge in this area (Johnson, 

1995). 

Aside from its theoretical implications, the extent to which offenders escalate into 

more serious crimes over time may prove useful for informing policy deliberations. To 

the extent that careers in intimate partner violence escalate in seriousness with offenders 

moving to increasingly more serious intimate partner violence as they proceed from one 

13

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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. 
14

 

arrest to another, then crime control strategies that are effective in interrupting the normal 

progress of martial violence careers would be especially beneficial in reducing 

subsequent serious crimes (Blumstein et al., 1988). We view this research as a useful 

step in strengthening the knowledge base necessary for sound development of theory and 

policy. 

Data 

 To examine these questions, we use data from the Spouse Assault Replication 

Program (SARP). The SARP was originally designed to replicate the Minneapolis 

domestic violence experiment conducted by Sherman and Berk (1984). In the 

Minneapolis study (n=314), Sherman and Berk compared repeat domestic violence rates 

for cases where the offender was arrested to cases where the police responded informally 

in one of two ways, advisement or separation. In the advisement condition, the police left 

the home only after advising the couple to calm down, while in the separation condition 

the police ordered the suspect to leave the home for eight hours. The project only applied 

to simple (misdemeanor) domestic assaults where both the suspect and the victim were 

present when the police arrived (Sherman and Berk, 1984).3

The results of the Minneapolis study indicated that arresting domestic violence 

suspects led to a lower risk of repeat domestic violence, and this was the case in both 

3

 According to Sherman (1992:272): “The design called for each officer to carry a pad of report forms, 

color coded for the three different police responses. Each time the officers encountered a situation that fit 

the experiment’s criteria, they were to take whatever action was indicated by the report form on the top of 

the pad. The forms were numbered and arranged for each officer in an order determined by the lottery. The 

consistency of the lottery assignment was to be monitored by research staff observers riding on patrol for a 

sample of evenings. After a police action was taken at the scene of a domestic violence incident, the officer 

was to fill out a brief report and give it to the research staff for follow-up. As a further check on the lottery 

process, the staff logged in the reports in the order in which they were received and made sure that the 

sequence corresponded to the original assignment of responses.” 

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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. 
official and victim interviews. More specifically, arrest and a night in jail cut in half the 

risk of repeat violence against the same victim over a six-month follow-up period 

(Sherman, 1992:2). Because the study relied on randomized treatment assignment, its 

internal validity was strong.4

To examine the external validity of this result, in 1986 the National Institute of 

Justice funded replications of the Minneapolis experiment in six other cities in 

geographically diverse regions around the United States including Atlanta, Charlotte 

(n=650), Colorado Springs (n=1,658), Miami-Dade (n=907), Milwaukee (n=1,200), and 

Omaha (n=330), which also contained a second experiment that tested the issuance of 

arrest warrants in cases in which suspects had left the home before police arrived (i.e., the 

“offender-absent” experiment) (Maxwell, Garner, and Fagan, 2002; Sherman, 

1992:15). The Atlanta project was never completed but the projects in the other sites 

were completed and we use data from all of them in our study. The implementation of 

the SARP studies and interpretation of the SARP findings have been described in detail 

by Garner, Fagan, and Maxwell (1995) and Maxwell et al. (2002). We provide some 

further information here. 

There were a number of important differences across the replication sites. First, 

only Omaha’s offender-present experiment actually replicated the original Minneapolis 

4

 As with any experiment, there were some difficulties in Minneapolis. According to Sherman (1992:12) 

many of the officers occasionally failed to follow fully the experimental design for a variety of reasons 

including forgetfulness, misunderstanding about whether the experiment applied in certain situations, or 

officers dropping out of the experiment. Also, there were difficulties associated with getting the victims to 

grant follow-up interviews to report any repeat violence. Treatment-designed and treatment delivered was 

highest in the arrest condition (98.9%), and fairly high in the advise (77.8%) and separate (72.8%) 

conditions (Sherman, 1992:274). Because arrest became a fallback position, the ‘more difficult’ offenders 

who did not comply with the other conditions were arrested, thus biasing against finding a deterrent effect 

of arrest (see Sherman, 1992:275). 

 

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15
16

research design; the other experiments, while replicating the random arrest/no-arrest 

assignment component of Minneapolis, tested different treatments or combinations of 

treatments (Sherman, 1992:15). Second, the replication experiments forced the officer to 

call a dispatcher for a random assignment of police response. In Minneapolis, the officer 

knew what the assignment would be because of the colored paper. Third, there were 

alternative treatments included. For example, in Milwaukee the mediation and separation 

components of the original Minneapolis experiment were omitted in favor of comparing a 

standard verbal warning to two different lengths of time in custody after arrest (three 

versus twelve hours) (Sherman, 1992:16). In Colorado Springs, arrest was compared to 

two alternatives: immediate professional counseling at police headquarters and issuance 

of an emergency protection order formally barring the suspect from the premises 

(Sherman, 1992:16). In Charlotte, arrest was compared to either mediation or separation 

and to issuing a ticket at the scene requiring the suspect’s presence in court on a future 

date, while in Miami-Dade, arrest was compared to no-arrest, both with and without 

follow-up counseling by a specially trained police unit that visited the home a few days 

after the incident (Sherman, 1992:16). Fourth, the replication sites were comprised of 

very different ‘types’ of samples. For example, married couples were more common in 

Miami (79%) and Colorado Springs (69%), while uncommon in Milwaukee (30%) and 

Minneapolis (35%). Black suspects were most common in Milwaukee (75%) and 

Charlotte (70%), and least common in Colorado Springs (31%). Unemployment of 

suspects was most prevalent in Minneapolis (60%) and Milwaukee (47%). High-crime 

area samples were common in Minneapolis and Milwaukee. And finally, sample sizes 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
varied from a low of 314 in Minneapolis to a high of 1,658 in Colorado Springs. Fifth, 

the replication findings were mixed. For example, in three cities (Minneapolis, MiamiDade, and Colorado Springs) a deterrent effect was observed while in the three other 

cities (Milwaukee, Omaha, and Charlotte), arrest backfired causing an escalation effect. 

Additionally, arrest seemed to work different depending on the constellation of individual 

characteristics. Specifically, arrest deterred employed suspects in Omaha, Milwaukee, 

and Colorado Springs, but backfired (led to escalation) in those three cities for 

unemployed suspects. Additionally, in three cities (Omaha, Charlotte, and Milwaukee) 

there was a six-month deterrent effect in the official records, but this deterrent effect 

decayed over time such that between six- and twelve-months, the official measures in 

these three cities provided evidence of escalation. Finally, the offender-absent 

experiment in Omaha provided very strong evidence of a deterrence effect for warrant 

group compared to the no-warrant group. 

Two particular aspects of the SARP data are important for our purposes. First, the 

SARP data contain information on arrest activity prior to the incident in which the 

offender entered the experiment (i.e., the presenting incident). This information takes the 

form of frequency distributions but it does divide the types of offenses into property, 

violent, and other crimes. These data will allow us to examine whether individuals 

entering the experiments exhibit specialization in violence. Second, the data contain 

detailed information from victim interviews on the nature of the violence occurring at the 

presenting incident as well as the nature of the violence occurring at subsequent points in 

time after the presenting incident. With these data, we will examine the extent to which 

the severity of offenders' attacks against the same victim increases, decreases, or stays 

17

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18

about the same. Specifically, we will use data from the SARP to answer two questions: 

(1) to what extent do individual domestic violence suspects exhibit specialization in 

violent offending behavior?; and (2) to what extent do individual domestic violence 

suspects increase, decrease, or maintain the severity of their attacks on the same victim 

over time? 

 We will discuss the results for each of our two research questions separately for 

each of the sites. We begin with a description of the analytic methods we use in this 

study. Next, we turn to a discussion of the specialization question using official arrest 

data from the Charlotte, Colorado Springs, Milwaukee, and Omaha sites. We were 

unable to locate detailed information on prior arrest records of the domestic violence 

suspects in the Miami-Dade study so it is not included in this part of the study. Next, we 

present the results of our escalation study using victim interview data from the Charlotte, 

Miami-Dade, Milwaukee, and Omaha sites. As noted by Maxwell, Garner, and Fagan 

(2002:54, 60), the interviews in Colorado Springs were conducted in a different manner 

than the interviews in the other sites. To maintain a high level of comparability between 

the sites, we elected not to include the Colorado Springs interview data in our analysis. 

After describing each of the site-specific results, we summarize our findings by 

conducting a formal comparison of our parameter estimates between the sites.5

Analytic Plan 

 Our specialization analysis focus is on estimating the conditional probability that 

an individual entering the experiment with a prior record has experienced arrests 

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. 
exclusively for violent criminal behavior, sv. We refer to this conditional probability as a 

specialization parameter because it measures the proportion of individuals with prior 

records who are violent specialists. Because our task is an inferential one, we are 

concerned with obtaining a point estimate of the specialization parameter but we are also 

concerned with understanding the amount of uncertainty surrounding the parameter 

estimate. Criminologists conventionally use standard errors and significance tests for 

expressing uncertainty about parameter estimates but, as Maxwell and his colleagues 

(2002:64) observed, "the use of statistical significance tests is technically not appropriate 

for nonprobability samples such as those used in the Minneapolis and SARP 

experiments." Such tests and indices are even less useful when sample sizes are small 

(say below 20-30 cases) as they are in some of the analysis results described in this paper. 

Furthermore, some of our specialization, escalation, and de-escalation parameters are 

estimated close to the boundary of the parameter space (i.e., 0 or 1). Conventional 

confidence interval calculations fail in this setting but they are not problematic for 

Bayesian posterior probability interval estimation. 

 Our analytic method avoids the ambiguities of interpreting significance tests and 

standard errors that plague much of the domestic violence literature based on 

nonprobability samples. Instead, we rely on a Bayesian framework which provides us 

with parameter estimates and uncertainty measures that are easy to interpret. 

Furthermore, there are no difficulties created by small sample sizes; there will simply be 

greater uncertainty in the analysis results. The Bayesian framework used here is 

5

 Since the original SARP experiments did not exclude on gender, we did not impose any such exclusion in 

our analysis. 

 

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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. 

19
particularly appropriate for scientific problems where only one or two parameters need to 

be estimated. This is because the method is computationally intensive and is much more 

difficult to implement in cases where many parameters need to be estimated. 

 Our main task in the specialization analysis is to use the official records available 

in the SARP data to infer the probability distribution of the specialization parameter, sv, 

for each of the sites. In each site, we begin by identifying the arrest records of each of 

the suspects entering the experiment. We then divide each of the N suspects into one of 

two groups: those with a prior arrest record, Np, and those without a prior arrest record, 

Np'. The population of interest to us includes those with a prior arrest record which is 

comprised of Np individuals. Within that population, we divide each of the Np individuals 

into two groups: those who have exclusively violent arrests, nv, and those with other 

types of activity, nv', in their records. With these terms in hand, we turn next to the 

analytic framework for our specialization analysis. 

 We do not and cannot definitively know the tendency of offenders to specialize in 

violence, sv, but we can estimate the probability distribution of that tendency and take as 

our point estimate the value of sv that maximizes the conditional probability of sv given 

the observed official record data, p(sv | Np,nv). Like all conditional probabilities, this 

conditional probability can be solved with Bayes' theorem: 

p sv | Np ( ) ,nv = p Np ,nv |s ( )v × p s( )v

p Np ,nv |s ( )v × p s( )v ds ∫ v

 (1) 

where p Np ,nv |s ( v ) is the likelihood function for a binomial problem with Np trials and nv

events. Eq. (1) gives the posterior probability distribution of sv after conditioning on the 

20

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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. 
observed official record data. The binomial likelihood function for this problem is given 

by: 

p Np ,nv |s ( )v = Np

nv

⎛

⎝ ⎜ 

⎞

⎠ ⎟ × sv

nv × 1− s ( )v

Np −nv

which is straightforward to implement. It is less straightforward to obtain a distribution 

for and to numerically evaluate the integral in the denominator of eq. (1). In the 

Bayesian framework, the distribution of 

p s( )v

p s( v ) is called a prior distribution because it is 

not supplied by the data (Iversen, 1984:18-34). We solve the problem of specifying the 

distribution of p s by assuming that s ( )v v can only take on discrete values in the interval 

[0.001, 0.999]. Next, we assume that p s( v ) is uniform or equal at each value in the 

sample space: 

p s( ) v = 0.001 = p s( ) v = 0.002 = ...= p s( ) v = 0.999 = 1

999

which implies that we believe each possible value of sv is equally probable before we 

examine the observed data. 

This assumption leads to an important simplification of eq. (1) which we use in all 

of our analyses: 

p sv = j | Np ( ) ,nv = p Np ,nv |s ( ) v = j × p s( v = j)

p Np,nv |s ( ) v = j × p s( ) v = j

j ∈[ ] 0.001,0.999

∑ , j = 0.001, 0.002,..., 0.999 (2) 

and the value of j that maximizes the posterior probability of sv, p(sv | Np,nv), is called the 

maximum posterior probability estimate of sv. Entering each value of j from the above 

sample space into eq. (2), and the binomial likelihood below: 

21

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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. 
p Np ,nv |s ( ) v = j = Np

nv

⎛

⎝ ⎜ ⎞⎠ ⎟ × j

nv × ( ) 1− j Np −nv

we calculate the posterior probability of sv so that the maximum posterior probability 

estimate of sv is the estimated value of sv that is most probable after conditioning on the 

data. This is an intuitively attractive rationale for choosing an estimate, but this method 

will produce the same point estimate as standard methods for calculating proportions and 

probabilities. We prefer this method because it provides us with an estimate of the full 

probability distribution for sv. With this distribution in hand, we can interpret a 95% 

probability interval for the distribution of sv to mean that there is a 95% probability that sv

lies in an interval bounded by [svL,svH]. A 95% confidence interval calculated under 

assumptions of simple random sampling cannot be interpreted in this fashion (Iversen, 

1984:11). In addition, some of our parameter estimates will be very close to zero 

implying a lower 95% confidence limit that is less than zero which is impossible for a 

probability parameter. The 95% probability interval produced by the calculations 

presented above does not suffer from this defect. Most importantly, a clear interpretation 

of the 95% probability interval is necessary for our purposes because we will be 

comparing our specialization analysis results across the different study sites. 

 Our analysis of escalation and de-escalation of attack severity involves analytic 

issues that are similar to those encountered in the specialization analysis. But the 

escalation and de-escalation analyses presented in this paper rely on the victim interviews 

about violence after the presenting incident rather than the official records which focused 

22

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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. 
on the arrest records of suspects prior to the presenting incident.6

 

Each of the sites made an effort to interview the presenting incident victims. The 

interviews asked victims who agreed to participate in the survey to describe the level of 

injury they experienced during the presenting incident. We divided the population of 

respondents, Nr, into two groups: (1) those who experienced an injury as a result of the 

attack, Ni; and (2) those who did not experience an injury, Ni'. The interviews also asked 

respondents whether there had been any new attacks between the presenting incident and 

the interview. Although we will define "injury" within the context of each study below, 

we note that for purposes of this study, we only count injuries as incidents resulting in 

cuts, bruises, scratches, unconsciousness, broken bones, broken teeth, eye and ear 

injuries, knife wounds, or gunshot wounds. This definition excludes slapping, pulling 

hair, punching, pushing or shoving, threats, and other attacking behaviors unless they 

produce one or more of the types of injuries listed above on the victim. This definition of 

injury, though arbitrary, sets a high but still quite frequently attained threshold for an 

incident to be classified as an injury-producing. 

So, each of the two populations, Ni and Ni' is comprised of two subpopulations: 

(1) those who experienced a new attack, Ni1 and Ni1'; and (2) those who did not 

experience a new attack, Ni0 and Ni0'. Our focus in the escalation and de-escalation 

analyses will be on the individuals comprising the population of victims who reported at 

least one new attack in their interviews, Ni1 and Ni1'. 

6

 There is no clear indication from the data or codebooks that the victim interviews were contingent on the 

original victim-offender relationship. Thus, in every case analyzed, there was no specific assumption or 

requirement that the victim was still in a relationship or residing with the offender after the initial, reported 

incident. 

 

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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. 

23
Consider the population of victims who experienced no injury in the presenting 

incident attack but who went on to participate in the survey and report a new 

victimization. Designating this population by Ni1', we divide each individual in that 

population into two groups: (1) those who experienced an injury in at least one of their 

new victimizations, ni1; and (2) those who did not experience an injury in any of their 

new victimizations, ni1'. Therefore, Ni1

' = ne + ne

'

 where ne identifies the population of 

people who experience an escalation in the severity of attacks against them by the 

suspect. The escalation parameter, e, measures the conditional probability that an 

individual who was victimized without injury at the presenting incident and who went on 

to experience at least one new victimization during the interview follow-up period is 

victimized with injury in at least one of those new victimization incidents. It follows that 

1 - e is the probability that an individual who experiences subsequent victimizations and 

who was victimized without injury at the presenting incident receives an injury in at least 

one of the subsequent victimizations reported on the interview. The posterior probability 

distribution is given by: 

p e = j | Ni1 ( ) ',ne = p Ni1',ne ( ) | e = j × p e( = j)

p Ni1',ne ( ) | e = j × p e( ) = j

j ∈[ ] 0.001,0.999

∑ , j = 0.001, 0.002,..., 0.999 (3) 

where the likelihood function in eq. (3) is given by the binomial distribution and is 

parameterized as: 

p Ni1',ne ( ) | e = j = Ni1'

ne

⎛

⎝ ⎜ ⎞⎠ ⎟ × j

ne × ( ) 1− j Ni1 '−ne

for each of the values of j above, and the prior distribution for e is given by: 

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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. 

24
p e( ) = 0.001 = p e( ) = 0.002 = ...= p e( ) = 0.999 = 1

999

to express our lack of prior information about the likely distribution of e. 

 Next, consider the population of victims who reported an injury in the presenting 

incident victimization and went on to report a new victimization after the presenting 

incident, Ni. We divide each of the cases into one of two groups: (1) those who 

experienced an injury in at least one of their subsequent victimizations, nd'; and (2) those 

who experienced no injury in any of their subsequent victimizations, nd. In symmetry 

with the escalation analysis, Ni = nd + nd' where nd represents the population of 

individuals who were victimized after the presenting incident in which the severity of the 

attack de-escalated from an attack with injury at the presenting incident to no attacks with 

injury after the presenting incident. The posterior probability distribution for the deescalation parameter, d, is given by: 

p d = j | Ni1 ( ) ,nd = p Ni1,nd ( ) | d = j × p d( = j)

p Ni1,nd ( ) | d = j × p d( ) = j

j ∈[ ] 0.001,0.999

∑ , j = 0.001, 0.002,..., 0.999 

and the likelihood function for all j is given by: 

p Ni1,nd ( ) | d = j = Ni1

nd

⎛

⎝ ⎜ ⎞⎠ ⎟ × j

nd × ( ) 1− j Ni1 −nd

and the prior distribution for d is given by: 

p d( ) = 0.001 = p d( ) = 0.002 = ...= p d( ) = 0.999 = 1

999

thus ensuring that all possible values of d (to three decimal places) have an equal 

probability before examining the data. Also in symmetry with the escalation analysis, the 

de-escalation parameter, d, measures the probability that an individual who reported 

25

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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. 
26

injury at the presenting incident and at least one subsequent victimization also reports no 

injury at the subsequent victimization. In addition, 1 - d represents the probability that an 

individual who reported injury at the presenting incident and a new victimization reported 

at least one injury inflicted by her abuser during the interview follow-up period. 

Specialization Analysis Results 

 In this section, we describe our substantive findings about the prevalence of 

specialized violent offending among suspects entering the SARP projects in Charlotte, 

Colorado Springs, Milwaukee, and Omaha. For each site, we will describe the data used 

for the analysis and we will present our parameter estimates. Then, we summarize our 

findings. 

Charlotte Analysis 

 The Charlotte SARP data used for this analysis are based on data from 650 unique 

suspects that entered the experiment between August 1987 and June 1989. There were 

36 cases where the same suspect entered the experiment twice (for a total of 686 cases); 

we focus exclusively on the 650 unique suspects. A frequency count of arrests for the 

following categories of offenses prior to the presenting incident were included in the 

data: (1) the number of arrests for an assault; (2) the number of arrests for other violent 

crimes; (3) the number of arrests for property crimes; and (4) the number of arrests for 

other types of crime. Categories (1) and (2) were summed to create a measure of the 

number of arrests for violent crimes and categories (3) and (4) were summed to create a 

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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. 
measure of the number of arrests for non-violent crimes.7

Next, each individual's offense history was examined to determine whether there 

were any prior arrests. This effort revealed that Np = 111 (17.1%) of the N = 650 

suspects had at least one prior arrest. The majority (86) of these 111 individuals had been 

arrested exclusively for property or other offenses while only 25 had been arrested for a 

violent offense. Out of these 25 cases, 11 suspects had been arrested for both violent and 

non-violent offenses in the past. The remaining 14 cases represent the population of 

violent specialists as they had been arrested exclusively for violent offenses in the past. 

Thus, our estimate of the prevalence of specialized violent offending in the Charlotte data 

is given by sv = 14

111 =12.6% (see Figure 1). The overwhelming majority of offenders 

with a prior arrest record in the Charlotte data have been involved in non-violent 

offending activity in addition to the violence that brought them into the SARP 

experiment. The 95% probability interval surrounding this point estimate is bounded on 

the low end by 0.077 (the 2.5%ile of the distribution) and on the high end by 0.200 (the 

97.5%ile of the distribution). 

Colorado Springs Analysis 

 The arrest data from the Colorado Springs study were obtained from a file that 

documents the pre-experiment arrest history for each of the suspects. Cases were 

enrolled between March 1987 and April 1989. There were a total of 1,548 cases in the 

file but 22 of these cases had duplicate suspect identification numbers. After deleting the 

7

 Two qualifications regarding the Charlotte data are in order. First, the Charlotte specialization analysis are 

based on data from state records only. Second, the state records only cover the five years prior to the 

reporting incident. 

 

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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. 

27
22 duplicates, one additional case that was missing some of the arrest information was 

deleted. This produced an analysis file with 1,525 unique suspects. The file contained 

frequency information on the number of counts charged for each of a wide variety of 

offense categories including felony assault, felony sexual assault, robbery, burglary, 

arson narcotics, third-degree assault, alcohol, menacing, harassment, false imprisonment, 

misdemeanor sexual assault, fighting, and other. Domestic counts of these same offenses 

were also collected. For purposes of this analysis, we treated felony assault, felony 

sexual assault, robbery, third-degree assault, false imprisonment, misdemeanor sexual 

assault, and fighting as violent offenses. We defined all other categories as non-violent 

offenses.8

 Analysis of the prior record data identified Np = 624 individuals (40.9% of 1,525) 

with at least one prior arrest. Among these 624 individuals, only nv = 41 ( 41

624 = 6.6%) 

could be characterized as violent specialists (i.e., all prior arrests for violent offenses). 

The modal category was non-violent offenses (332 suspects) followed by the generalist 

category comprised of 251 suspects who had been charged with violent and non-violent 

offenses in the past. Figure 2 presents the posterior distribution of the violent 

specialization parameter. The density peaks at 6.6% but an interesting feature of this 

distribution is the extent to which it is compressed around the maximum posterior point 

estimate; the lower bound of the 95% probability interval is 0.048 and the upper bound is 

0.087. The Colorado Springs interval is considerably narrower than the Charlotte interval 

8

 As in any analysis that places distinct offenses into more general categories, some readers may offer 

different categorization schemes (i.e., placing robbery in the non-violent category). We attempted to 

 

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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. 

28
but, importantly, the intervals for the two sites do overlap to some extent. 

closely follow much of the previous criminal careers research in our categorization scheme, but recognize 

that other decisions are equally appropriate. 

Milwaukee Analysis 

 The Milwaukee study enrolled 1,200 eligible domestic assault cases between 

1987 and 1989. Some of the cases involved suspects who made repeat appearances in the 

study. After deleting the duplicate records of multiple appearance suspects and one case 

with some missing offense information, we were left with an analysis file comprised of 

1,124 unique suspects. Information about the prior arrest records for each of the suspects 

was summarized in frequency count form. Thus, for each individual, information about 

the total number of prior arrests for theft, domestic violence, drug offenses, all other 

violent offenses, and all other offenses were available. We classified domestic violence 

and all other violent offenses as violence and we treated all the other categories as nonviolent offenses. 

Analysis of the data revealed that 467 suspects had no prior record while the 

remaining Np = 657 (58.5%) had at least one prior arrest. Nearly half of these suspects 

(307; 46.7%) had records exhibiting involvement in both violent and non-violent 

offending activity while another 196 suspects (29.8%) had records comprised entirely of 

non-violent offenses. The final 154 cases (sv = 23.4%) represent the population of violent 

specialists (nv) in the Milwaukee data. Figure 3 presents the posterior distribution of the 

violent specialization parameter which indicates a tight 95% probability interval 

bounding the maximum posterior estimate. The lower bound of the interval (2.5%ile) is 

0.203 and the upper bound (97.5%ile) is 0.268. This distribution is substantially higher 

 

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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. 

29
than what we observed in Colorado Springs. In addition, the lower bound of the 

Milwaukee interval slightly exceeds the upper bound of the Charlotte interval. 

Omaha Analysis 

 A total of 621 cases entered the Omaha experiment between March 1986 and 

September 1987 but 44 of these cases were generated by repeat instances of criminal 

domestic violence. The twelve-month criminal history file from the project contains data 

on 577 unique suspects and the exact dates of each arrest. The criminal history file was 

merged with a police report file so the date of each arrest could be compared with the 

presenting incident date. Some of the arrests reported in this file occurred after the 

presenting incident. It turns out that our analysis results change somewhat depending on 

whether we include the arrests occurring after the presenting incident. 

Considering only those arrests occurring before the presenting incident, Np = 363 

individuals had at least one arrest while the remaining Np' = 214 individuals did not. 

Among the 363 suspects with a prior arrest record, 217 individuals had been arrested only 

for non-violent offenses while 130 individuals had been arrested for both violent and 

non-violent offenses. The remaining nv = 16 individuals had been arrested exclusively 

for violent offenses in the past. This implies that the maximum posterior estimate of 

sv = 16

363 = 4.4%. Figure 4 presents the full posterior distribution of sv using only those 

arrests occurring before the presenting incident date. This is the lowest estimate we have 

seen in any of the SARP data sets but it is close to the estimates produced in the Colorado 

Springs analysis and the 95% probability intervals for the two sites exhibit considerable 

overlap. 

30

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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. 
It is straightforward to estimate sv including the full arrest history up to and 

including the year after the presenting incident so we conducted a second analysis to 

study this distribution. After including these additional arrests, we found that Np = 463 

individuals had experienced at least one arrest while Np' = 114 individuals had not. 

Within the population of arrested individuals, 147 (31.7%) had been arrested exclusively 

for non-violent offenses while 252 (54.4%) individuals had been arrested for both violent 

and non-violent offenses. The remaining nv = 64 individuals had been arrested 

exclusively for violent offenses producing a maximum posterior estimate of 

sv = 64

463 =13.8%. The full posterior distribution of sv is presented in Figure 5. The 95% 

probability interval has a lower bound of svL = 0.109 and a upper bound of svH = 0.172. 

Although there is an increased level of violent specialization in this second analysis, it is 

also true that the overwhelming majority of suspects do not exhibit specialized violent 

offending in their arrest records in either of the two Omaha analyses. 

Summary of Specialization Analysis Results 

 On balance, our review of SARP suspect arrest records indicates that most 

offenders do not engage in specialized violent offending. Of those who have been 

arrested, the vast majority have been arrested for non-violent offending over and above 

any arrests for violence they may have experienced. Table 1 summarizes the details of 

each of the analyses while Figure 6 shows the site-to-site variation in the posterior 

distribution of the specialization parameter. Despite this site-to-site variation, a basic 

story of low violence specialization consistently emerges. The highest levels of violence 

specialization were found in Milwaukee (sv = 0.236) while the lowest levels were found 

31

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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. 
32

in Omaha (pre-presenting incident analysis, sv = 0.044) and Colorado Springs (sv = 

0.066). The Charlotte estimate occupied an intermediate position but because of the 

relatively small number of cases available for study in this site, the posterior probability 

distribution is flatter than the other sites reflecting greater uncertainty about the parameter 

estimate. 

Escalation and De-Escalation Analysis Results 

 We now turn to our analysis of the SARP victim interview data to study 

escalation and de-escalation in the severity of attacks against the same victim after the 

presenting incident. In each of the sites, efforts were made to interview victims about the 

level of injury they experienced during the presenting incident. Victims were also 

interviewed about the level of injury experienced in new assaults occurring between the 

presenting incident and the time of the interviews. Attempts were made to contact 

victims for an initial interview and a follow-up interview (except in Omaha where there 

were two follow-up interviews - six months and twelve months after the presenting 

incident). As mentioned earlier, the interviews in Colorado Springs were conducted 

differently than those in the other sites and those data are not analyzed here. Thus, 

interview data from each of the other sites was examined (Charlotte, Miami-Dade, 

Milwaukee, and Omaha). A summary of our escalation and de-escalation findings is 

presented at the end. 

Charlotte Analysis 

 In Charlotte, initial interviews were targeted for a one-month follow-up period 

and were obtained from 419 victims (61% of the 686 eligible cases) while six-month 

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' = 196 victims reported none of these injuries 

at the presenting incident. 

interviews were obtained for 324 victims (47% of the 686 eligible cases). A total of 415 

victims provided injury information on the initial interview, while 320 victims provided 

injury information on the six-month interview. Our initial focus is on questions that were 

asked about the presenting incident. Each victim was asked whether: (1) you were hit on 

the head and blacked out or knocked out; (2) you had any broken bones or teeth; (3) you 

had any scratches or bruises; (4) you were shot with a gun; and (5) you were cut with a 

knife. Victims who answered any of these questions with a "yes" were coded as having 

experienced an injury at the presenting incident. The analysis shows that Ni = 219 

(

219

415 = 52.7%) victims reported being injured in at least one of these ways at the 

presenting incident while the remaining Ni

 The initial interview also asks about new attacks during the period between the 

presenting incident and the initial interview. Victims who reported experiencing new 

attacks were asked about the first incident of violence, the most recent incident, and the 

most serious interim incident if there was at least one occurrence of interim violence 

between the first and most recent incidents. The injury questions asked about the 

presenting incident were also asked about repeat incidents. Among the Ni' = 196 victims 

who experienced no injury at the presenting incident, Ni1' = 26 ( 26

196 =13.3%) went on to 

experience a new attack before the initial interview while the other Ni0' = 170 did not. 

For this group of 26 victims, we estimate the probability of experiencing at least one of 

the above-listed injuries. The maximum posterior estimate of this probability is given by 

33

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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. 
e = ne

Ni1'

= 18

26 = 0.692 which indicates that the majority of those who escaped the 

presenting incident without injury but went on to experience a new attack before the 

initial interview reported being injured on the interview. 

 The six-month interview asks victims about new victimizations since the initial 

interview. It asks about the first and most recent victimization as well as about interim 

victimization between the first and most recent victimizations. The injury questions on 

the six-month interview are the same as those used in the initial interview. Our analysis 

of the six-month interview data includes only those individuals participating in the sixmonth interview but injury questions from both the initial and the six-month interview 

were used to classify individuals as having been injured in a new attack by the time of the 

six-month interview. So, an individual who is characterized as being a victim of injury 

escalation at the initial interview was characterized as a victim of injury escalation 

through the six-month interview even if no additional injuries were reported on the sixmonth interview. Individuals who did not complete the six-month interview were not 

included in the analysis regardless of their injury status at the initial interview. 

 Out of the 320 individuals who provided information about injury through the sixmonth interview, Ni =172 ( 172

320 = 53.8%) reported experiencing an injury at the 

presenting incident. The remaining Ni' = 148 reported no injury at the presenting 

incident. Among those victims who were not injured at the presenting incident, Ni1' = 43 

( 43

148 = 29.1%) reported experiencing a new attack between the presenting incident and 

the six-month interview. Within this group of repeat victims who experienced no injury 

34

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
at the presenting incident, we estimate the probability of injury, which, for this group, is 

the probability of escalation bye = ne

Ni1'

= 36

43 = 0.837. In both the initial and the sixmonth interviews in Charlotte, then, there is evidence of significant escalation between 

the presenting incidents and the time of the interviews. Figure 7 presents the full 

posterior probability distribution for both of the Charlotte escalation parameters based on 

the initial and six-month interview analyses. 

 We now turn to an analysis of de-escalation within the group of Ni = 219 victims 

who reported experiencing an injury in their presenting incident victimization on the 

initial interview. The initial interview data reveal that Ni1 = 52 ( 52

219 = 23.7%) of these 

individuals experienced a new attack by the time of the initial interview. Within this 

group of repeat victims, 45 ( 45

52 = 86.5%) went on to be injured again while nd = 7 were 

not injured again and are, therefore, classified as experiencing de-escalation. Thus, the 

maximum posterior estimate for the de-escalation parameter within this population is 

given by d = nd

Ni1

= 7

52 = 0.135. 

 At the six-month interview, our base population for studying de-escalation is the 

Ni = 172 individuals who experienced an injury at the presenting incident and participated 

in the six-month interview. Within this group of victims, Ni1 = 77 individuals report at 

least one new victimization between the presenting incident and the six-month interview. 

In this population, we estimate the proportion of individuals who are not injured; this will 

be our estimated probability of de-escalation. The data indicate that nd = 6 out of the 77 

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. 
victims in this group were not injured. This implies that the maximum posterior 

estimated de-escalation probability is d = nd

Ni1

= 6

77 = 0.078. The full posterior 

probability distributions for the initial and six-month interview-based de-escalation 

parameters are presented in Figure 8. In both sets of analyses the prevalence of deescalation is quite close to zero. Taken together with the escalation findings, the weight 

of the evidence suggests that new attacks have a relatively high likelihood of being 

accompanied by new injury to the victim. 

Miami-Dade Analysis 

 The Miami-Dade study enrolled 907 eligible cases between August 1987 and 

January 1989. Documentation associated with the data files indicates that initial 

interviews were completed with 595 victims and six-month interviews were completed 

with 395 victims. When we merged the initial interview and six-month interview files, 

607 unique cases were identified. Twelve of these 607 cases had information from the 

six-month interview but no information from an initial interview. We deleted these 

observations plus one additional observation that had missing data on the gateway 

victimization question on the initial interview. This left us with an initial interview 

database comprised of 594 victims. After deleting individuals who appeared in the initial 

interview database but not in the six-month interview database plus one additional person 

with missing information on the six-month victimization gateway question we were left 

with a six-month database comprised of 371 victims. 

 At the initial interview, victims were asked a number of questions about the 

presenting incident including the level of injury experienced as a result of that incident. 

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. 
Injury items included the following: (1) loss of consciousness (blackout); (2) internal 

injuries; (3) gunshot wound; (4) knife wound; (5) eye or teeth injury; (6) broken 

bones/dislocated joints; (7) concussion/bump on head; (8) serious cuts, bruises or burns; 

and (9) minor cuts, scratches/bruises. Out of the 594 victims interviewed, 403 (67.8%) 

reported having received at least one of these injuries while the remaining 191 (32.2%) 

victims reported receiving none of these injuries. 

 The initial interview also asked victims about attacks between the presenting 

incident and the interview. Detailed information about the first two attacks was solicited 

including information about injuries experienced by the victim. The items used on the 

injury scale above were also used to characterize injuries for subsequent attacks. 

 We first consider the results of our escalation analysis. Out of the 191 victims 

reporting no injury at the presenting incident, Ni1' = 12 reported at least one new attack 

before the initial interview; thus, the prevalence of revictimization within this population 

was 6.3%. Our focus in this analysis is on how many of the 12 victims reported an injury 

on the initial interview; such cases are construed as escalations because they move from a 

no-injury status at the presenting incident to an injury status on the initial interview. The 

analysis reveals that ne = 2 of these twelve individuals reported an injury yielding a 

maximum posterior estimate of e = 2

12 = 0.167. 

 Moving to the six-month follow-up, victims were asked detailed questions about 

the first incident of violence that occurred between the initial and the six-month 

interviews. The injury scale used above was also used on the six-month interview. 

Within the population of 371 respondents, 117 victims reported no injury at the 

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. 
presenting incident. Within this group, 23 victims (19.7%) reported at least one new 

attack by the six-month interview. Out of these 23 victims, ne = 7 reported experiencing 

an injury implying a maximum posterior escalation estimate of e = 7

23 = 0.304 . The full 

posterior distributions for both of the Miami-Dade escalation parameters are presented in 

Figure 9. The small number of cases involved in this analysis means that these 

distributions are highly dispersed. In fact, the posterior probability of the point estimates 

are lower for these escalation parameters than for any of the other parameters estimated 

in this paper. 

 We now address the issue of de-escalation in the Miami-Dade data. At the initial 

interview, Ni = 403 out of the 594 victims (67.8%) reported experiencing at least one of 

the above-named injuries at the presenting incident. Our analysis identifies this 

population as the set of individuals who could potentially experience de-escalation. 

Within this population of 403 victims, Ni1 = 72 (17.9%) reported at least one new attack 

by the initial interview. Our analysis reveals that nd = 30 of these victims did not 

experience an injury while the remaining nd' = 42 did. Thus, the maximum posterior 

estimate of the initial interview-based de-escalation parameter is d = 30

72 = 0.417. 

 Analysis of the six-month interview data, revealed that Ni = 254 of the 371 

victims (68.5%) reported an injury as a result of the presenting incident. Combining 

information from the initial and six-month interviews, Ni1 = 75 of these victims reported a 

new attack between the presenting incident and the follow-up interview. Among these 75 

victims, nd = 33 reported no injury as a result of new attacks while the other nd' = 42 

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. 
reported at least one new injury. This implies an estimated de-escalation probability of 

d = 33

75 = 0.440. The full posterior distributions for both the initial-interview and sixmonth interview-based measures of de-escalation are presented in Figure 10. These 

estimated distributions overlap closely and indicate that individuals who were injured at 

the presenting incident and who experienced one or more new attacks had a 40-45% 

chance of reporting no injury (de-escalating) on the survey. 

Milwaukee Analysis 

 The Milwaukee project did not attempt to conduct an initial interview with all 

victims. As Maxwell, Garner, and Fagan (2002:54) point out, "25% of victims were not 

interviewed until six months after the presenting incident." The database documentation 

states that "a total of 705 initial interviews were conducted from the 1,200 eligible 

domestic battery incidents." Our inquiry into the initial interview database revealed five 

individuals with missing information on the injury questions associated with the 

presenting incident. Our initial interview analysis database is comprised of the remaining 

700 victims and our six-month interview database will be comprised of the subset of 599 

of these 700 victims who go on to participate in the six-month interview. The initial 

interview queried victims about new attacks after the police response (different sets of 

questions for informal treatment and arrested cases), and then about the first and most 

recent attacks (not including a reunion incident if one occurred). At the six-month 

interview, victims were asked about the first and most recent attacks following the 

presenting incident. At the presenting incident and the follow-up incidents, victims were 

asked about the following injuries: (1) internal injuries; (2) scratches, cuts, bruises; (3) 

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. 
concussion; (4) broken bones/teeth; (5) knife wound; and (6) gunshot wound. 

 At this initial interview, Ni' = 170 (24.3%) victims reported receiving no injury at 

the presenting incident while the remaining Ni = 530 (75.7%) victims reported receiving 

at least one of the above injuries at the presenting incident. The Ni' = 170 victims 

reporting no injury at the presenting incident constitute our population at risk of injury 

escalation. A total of Ni1' = 47 individuals reported experiencing a new victimization by 

the time of the initial interview. But only three of these new attacks was accompanied by 

an injury yielding a maximum posterior escalation estimate of e = 3

47 = 0.064 . 

At the six-month interview, the N = 599 participants can be divided into two 

groups: (1) the Ni = 457 victims who reported an injury due to the presenting incident; 

and (2) the Ni' = 142 victims who reported no injury due to the presenting incident. The 

group of Ni' = 142 is the population at risk of escalation. The analysis identified Ni1' = 62 

individuals who reported a new victimization between the presenting incident and the sixmonth interview. An examination of the injury data indicated that the proportion of these 

Ni1' = 62 victims who reported an injury was e = 22

62 = 0.355. Figure 11 presents the full 

posterior probability distribution for both the initial- and six-month interview-based 

estimates of the escalation parameter. 

 As noted above, Ni = 530 (75.7% of N = 700) victims reporting an injury at the 

presenting incident were identified. Among these Ni = 530 victims, Ni1 = 126 (23.8%) 

reported a new attack between the presenting incident and the initial interview. Our 

maximum posterior estimate of the de-escalation parameter for this population is the 

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. 
proportion of these 126 victims who report receiving no injury in a follow-up attack; in 

this instance, that estimate is given by: d = 91

126 = 0.722. When we consider the sixmonth interview, however, this estimate drops considerably. 

 The six-month interview followed up N = 599 victims of whom Ni = 457 (76.3%) 

reported an injury from the above list at the presenting incident. Nearly half of these 

victims (Ni1 = 212; 46.4%) reported being revictimized between the presenting incident 

and the six-month interview. Within this group of repeat victims, nd = 81 reported 

experiencing no injury as a result of their repeat victimization; our maximum posterior 

estimate of de-escalation is given by d = 81

212 = 0.382. Contrary to the initial interview 

inference, this result implies that the majority of the repeat victims were, in fact, 

experiencing new injuries. The full posterior distribution for both the initial- and sixmonth interview-based estimates of the Milwaukee de-escalation parameter are presented 

in Figure 12 and highlight the different inferences produced by the two sets of interview 

results. 

Omaha Analysis 

 The Omaha protocol included three interviews for each victim agreeing to 

participate. The initial interview (N = 477), targeted for one week after the presenting 

incident asked detailed questions about that incident including whether they experienced 

each of the following injuries: (1) bruised/scratched; (2) cut/bleeding; (3) unconscious; 

(4) broken bones; and (5) head injuries. 

Interviews conducted approximately six months (N = 438) and one year (N = 416) 

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. 
after the presenting incident asked questions about attacks occurring after the presenting 

incident. The six-month interview asked detailed questions about each of the first three 

incidents after the presenting incident while the one-year interview asked detailed 

questions about each of the first three incidents occurring after the six-month interview. 

The follow-up interviews asked slightly different questions about injuries than the initial 

one-week interview: (1) bruised/scratched; (2) cut; (3) knocked/choked unconscious; and 

(4) teeth/eyes/ears injured. 

 Using information provided by the N = 438 six-month interview respondents, we 

found that Ni = 335 (76.5%) reported they had been injured at the presenting incident 

while Ni' = 103 said they had not been injured at the presenting incident. Almost half of 

the Ni' = 103 noninjured victims went on to experience a new attack before the six-month 

interview (Ni1' = 51). Analysis of the injury data at the six-month interview revealed that 

ne = 20 of these 51 victims experienced one or more of the above-listed injuries yielding 

a maximum posterior escalation parameter estimate of e = 20

51 = 0.392. 

At the one-year interview, Ni' = 99 non-injured presenting incident victims 

remained and Ni1' = 60 (60.6%) of these victims had gone on to experience a new 

victimization between the presenting incident and the one-year interview. Out of these 

60 victims, ne = 26 went on to experience an injury; this implies that the probability of 

escalation within this group is e = 26

60 = 0.433. These estimates imply that nearly half of 

the Omaha victims who were not injured at the presenting incident went on to experience 

an injury if they encountered additional assaults. The full posterior distributions for the 

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. 
six-month and one-year escalation parameters are presented in Figure 13. 

As noted above, the majority of the Omaha respondents reported an injury at the 

presenting incident (Ni = 335 at the six-month interview and Ni = 317 at the one-year 

interview). Our analysis of the six-month and one-year follow-up information revealed 

that the majority of the respondents experienced at least one new attack (Ni1 = 202 at the 

six-month interview and Ni1 = 221 at the one-year interview). In both interviews, about 

half of the respondents experiencing a new attack reported an injury while about half did 

not ( d = 115

202 = 0.569 at the six-month interview and d = 111221 = 0.502 at the one-year 

interview). This result implies that de-escalation and stable injury victimization were 

approximately equally prevalent outcomes for those who experienced new victimizations. 

The full posterior distributions for the de-escalation parameters in the Omaha study are 

presented in Figure 14. 

Summary of Escalation and De-Escalation Analysis Results 

 Our escalation and de-escalation findings varied considerably from site-to-site. 

And, in some instances, our findings varied depending on the follow-up period within 

sites. Table 2 presents a summary of the escalation results and shows that, overall, the 

Charlotte analysis provides the highest escalation parameter estimates. In no other site, 

did the maximum posterior estimates of the escalation parameter exceed 50% (although 

some of the upper limits of the 95% probability interval did exceed 50%). The escalation 

parameter point estimates in the other sites - particularly at longer follow-up periods - 

seem to have settled in a range between 0.3 and 0.5 indicating that about one-third to onehalf of victims who (1) had not been injured at the presenting incident and (2) went on to 

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. 
44

experience a new attack were actually injured as a result of that attack. 

 As Table 3 indicates, the Charlotte analysis also produced outlying de-escalation 

parameter estimates. By the six-month follow-up interview in Charlotte only about 8% 

of those victims who experienced a new victimization and had been injured in the 

presenting incident escaped a subsequent injury. These estimates were substantially 

higher in the other sites (Miami-Dade = 44%; Milwaukee = 38%; and Omaha = 57% at 

six months and 50% at one year) indicating that in most sites the follow-up victimizations 

represented a mixed bag of injury seriousness in comparison to the injuries encountered 

in the presenting incident. 

Discussion 

 We began this analysis by asking two very basic criminal career questions that 

have escaped the research literature in domestic violence: (1) to what extent do domestic 

violence offenders exhibit a specialized tendency to engage exclusively in violent 

criminal behavior?; and (2) how prevalent are escalation and de-escalation in the 

seriousness of attacks by an offender against the same victim in a longitudinal sequence 

of criminal domestic violence? These are precisely the types of inquiries that National 

Research Council panels on Criminal Careers and Understanding and Preventing 

Violence have advocated (Blumstein et al., 1986; Reiss and Roth, 1993). The emphasis 

of our analysis has been to use the detailed official record and victim interview 

information collected by the SARP investigators to gain some insights into both 

parameters of domestic violence offenders' criminal careers. This is an important feature 

of our work because most criminal career/domestic violence studies do not integrate data 

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. 
from these two sources (i.e., official and self-report records). Our analysis of 

specialization and escalation in the SARP data has produced some interesting insights 

about both dimensions of the criminal careers of domestic violence offenders. 

 On the question of offending specialization, our analysis of official record data in 

Charlotte, Colorado Springs, Milwaukee, and Omaha indicates that few SARP domestic 

violence offenders have been specializing exclusively in violent criminal behavior. We 

were certainly able to identify many SARP offenders with violence in their official 

criminal histories, but the overwhelming majority of these individuals also had nonviolent offenses in their criminal histories. Consistent with many criminological theories 

and more general criminal careers research, our analysis suggests that criminal domestic 

violence is part of a larger cluster of serious problem behaviors in the lives of the people 

who commit it (e.g., Gottfredson and Hirschi, 1990). The domestic violence offender 

who is arrested only for violent criminal activity appears to be the exception rather than 

norm. 

 On the question of escalation and de-escalation in the seriousness of domestic 

violence, our analysis of victim interview data in the SARP sites of Miami-Dade, 

Milwaukee, and Omaha indicate that there is a heterogeneous mix of offenders who 

escalate and de-escalate the severity of their attacks over the relatively short-term followup periods covered by these studies. The exception site for both escalation and deescalation was Charlotte where tendencies of offenders to escalate the severity of attacks 

in low-injury presenting cases were pronounced and tendencies of offenders to deescalate the severity of attacks in high-injury presenting cases were virtually nonexistent. 

 There are some important limitations to our study. The first is an exclusive focus 

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. 
46

on official records to study the question of specialization. More effort needs to be 

devoted to research on specialization through the use of offender and victim interviews to 

gain a broader understanding of the role different types of criminal activity plays in the 

lives of domestic violence offenders (Blumstein et al., 1986; Lynam et al., 2004). 

 Second, the interview information we have is plagued by our inability to know 

how the results would have changed if rates of missing data had been lower (see e.g., 

Sherman, 1992; Brame, 2000). Interview-based studies of criminal domestic violence 

victims are always subject to more than the usual degree of caution exercised in most 

survey studies because the response rates are lower and item measurement properties are 

not well understood. It is certainly plausible to claim that non-interviewed victims have a 

different victimization experience than interviewed victims (Saphire, 1994; Stasny, 

1990:323-325; Stasny, 1991:302; Conaway, 1993:113; Kadane, 1985; Brame, 2000). As 

one reviewer commented, previous studies have shown that victims, when repeatedly 

surveyed, tend to underreport victimizations over time; this trend has implications for 

studying escalation of attacks when the only data used are victim reports. Unfortunately, 

official records will also suffer from the bias that they contain only a small snapshot of 

true, reported crime. 

 A third limitation has to do with our focus on comparatively less serious forms of 

domestic violence. This is based on the case selection criteria for the SARP studies 

which focused primarily on cases where the police maintain wide discretion about how to 

respond to the case (Maxwell et al., 2002). In general, for more injurious criminal 

domestic violence cases, the police are required by law to arrest and such cases were 

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. 
systematically excluded from the SARP studies. The criminal careers of felony domestic 

violence offenders might look quite different from those we have examined in this study. 

Fourth, this study lacked many data points for studying escalation/de-escalation, 

and it is unlikely the case that two points in time can be definitively considered a trend. 

To draw the conclusion that an offender has become less violent over time should depend 

on more data points. Unfortunately, such data in the domestic violence area are rare, and 

as such, we encourage further resources on this front. 

Finally, the SARP studies were designed to measure the short-term impact of 

arrest on the behavior of domestic violence offenders. But, it will be important going 

forward to trace the mix and progression of domestic violence offenders' criminal careers 

over longer follow-up periods. There is very little research examining the long-term 

careers of domestic violence offenders (see e.g., Sherman, 1992:212-246) but such 

research is badly needed. 

With these limitations in hand, we envision a healthy research agenda that moves 

our preliminary work forward. First, while our effort was designed to document patterns 

of specialization and escalation, we were unable to distinguish the correlates associated 

with different escalation trajectories. Researchers should attempt to document the factors 

that distinguish between escalators, de-escalators, and/or those who maintain high or low 

levels of domestic violence. Specific study of the factors that are associated with 

escalation to injury or even fatal violence have important public health implications. 

Second, while quantitative research can certainly document patterns of escalation and deescalation, qualitative studies are better suited to fill many of the holes in this line of 

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. 
48

 

research. For example, case study and/or life history efforts can provide rich information 

about how escalation works and the extent to which men deny or women inflate the 

extent and type of domestic assault. Third, it would be useful to further unpack the 

specialization and escalation parameters in an effort to determine if a particular stratifier 

leads to different estimates. For example, it may be that escalation/specialization vary 

according to the race of the suspect/victim, where the offenders were in the life-course 

when the study began (i.e., age), and/or according to whether some individuals have a 

higher likelihood of reporting domestic assault to the police. Fourth, our escalation 

analysis used a binary indicator of injury/no injury. Clearly, there are other methods of 

measuring injury such as an ordinal or even linear/Guttman metric and it would be useful 

to employ those approaches in subsequent research.9

 Finally, bearing in mind that 

patterns of escalation/de-escalation have been rarely studied in criminal careers research 

(Piquero et al., 2003), it would be particularly useful to examine how patterns of 

offending vary along the seriousness dimension over time among domestic violence 

offenders. 

In the end, this study provides us with a useful window on the mix and 

progression of criminal activities among domestic violence offenders in different parts of 

the United States. It tells us something about the generality of criminal behavior and the 

progression of domestic violence among offenders who abuse their partners. We hope it 

9

 A reviewer raised an interesting point about whether the severity of the assaults escalate or de-escalate 

over time using the definition of injury employed in this study. For example, if the victim had a bruise in 

the initial, reported incident and was stabbed by the perpetrator three months later, the data would be 

recorded as an injury each time with no distinction as to severity or escalation. This is a good observation. 

Future research efforts should attempt to use different operational definitions of injury to determine the 

sensitivity of our results. 

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. 
will spur efforts to advance our understanding of theory and policy to address the 

criminal domestic violence problem.

49

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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. 
50

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53

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. 
54

List of Tables 

Table 1: Summary of Specialization Results by Site 

Table 2: Summary of Escalation Results by Site 

Table 3: Summary of De-Escalation Results by Site 

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 Figures 

Figure 1: Posterior Distribution of Violent Specialization Parameter – Charlotte SARP 

Data. 

Figure 2: Posterior Distribution of Violent Specialization Parameter – Colorado Spring 

SARP Data. 

Figure 3: Posterior Distribution of Violent Specialization Parameter – Milwaukee SARP 

Data. 

Figure 4: Posterior Distribution of Violent Specialization Parameter – Omaha SARP Data 

– Pre-Presenting Incident Arrests Only. 

Figure 5: Posterior Distribution of Violent Specialization Parameter – Omaha SARP Data 

– All Arrests Through 12 Months After Presenting Incident. 

Figure 6: Full Posterior Distribution of Specialization Parameter by Site. 

Figure 7: Escalation Analysis from Initial and Six-Month Interviews – Charlotte SARP 

Data. 

Figure 8: De-Escalation Analysis from Initial and Six-Month Interviews – Charlotte 

SARP Data. 

Figure 9: Escalation Analysis from Initial and Six-Month Interviews – Miami-Dade 

SARP Data. 

Figure 10: De-Escalation Analysis from Initial and Six-Month Interviews – Miami-Dade 

SARP Data. 

Figure 11: Escalation Analysis from Initial and Six-Month Interviews – Milwaukee 

SARP Data. 

Figure 12: De-Escalation Analysis from Initial and Six-Month Interviews – Milwaukee 

SARP Data. 

Figure 13: Escalation Analysis from Six- and Twelve-Month Interviews – Omaha SARP 

Data. 

Figure 14: De-Escalation Analysis from Six- and Twelve-Month Interviews – Omaha 

SARP Data. 

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. 
Table 1

Summary of Specialization Results by Site

Site N= N

p

N

p

/N nv nv’ sv svL svH

Charlotte

Colorado Springs

Milwaukee

Omaha #1

Omaha #2

650

1,525

1,124

577

577

111

624

657

363

463

0.171

0.409

0.585

0.629

0.802

14

41

154

16

64

97

583

503

347

399

0.126

0.066

0.234

0.044

0.138

0.077

0.048

0.203

0.027

0.109

0.200

0.087

0.268

0.070

0.172

Notes:

N = Analysis Sample Size

N

p

 = Number of Individuals with Arrest Record

N

p

/N = Proportion of Sample With Arrest Record

nv = Number of Violent Specialists

nv

’ = N

p

 - nv

sv = nv/N

p

svL = Lower Bound of 95% Posterior Probability Interval for sv

svH = Upper Bound of 95% Posterior Probability Interval for sv

Omaha #1 refers to officially recorded charges prior to presenting incident; Omaha #2 refers to

offenses both before and after the presenting incident.

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 2

Summary of Escalation Results by Site

Site/Interview Ni’ Ni1’ Ni1’/Ni’ ne ne’ e eL eH

Charlotte (I)

Charlotte (6)

Miami-Dade (I)

Miami-Dade (6)

Milwaukee (I)

Milwaukee (6)

Omaha (6)

Omaha (12)

196

148

191

117

170

142

103

99

26

43

12

23

47

62

51

60

0.133

0.291

0.063

0.197

0.276

0.437

0.495

0.606

18

36

2

7

3

22

20

26

8

7

10

16

44

40

31

34

0.692

0.837

0.167

0.304

0.064

0.355

0.392

0.433

0.498

0.699

0.050

0.156

0.023

0.247

0.270

0.315

0.834

0.918

0.454

0.511

0.171

0.479

0.529

0.559

Notes:

(I) = Initial interview

(6) = 6-Month interview

(12) = 12-Month interview

Ni’ = Number of Interviewed Victims Without Injury at Presenting Incident

Ni1’ = Number of Individuals in Ni

’ Victimized Between Presenting Incident and Interview

Ni1’/Ni’ = Proportion of Ni’ With New Victimization Between Presenting Incident and Interview

ne

 = Number of Victims Reporting an Injury After Presenting Incident (Escalations)

ne’ = Ni1’ - ne (Number of Stable Non-Injury Victims)

e = ne

/Ni1’ (Escalation Parameter)

eL = Lower Bound of 95% Posterior Probability Interval for e

eH = Upper Bound of 95% Posterior Probability Interval for e

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 3

Summary of De-escalation Results by Site

Site/Interview Ni Ni1 Ni1/Ni nd nd’ d dL dH

Charlotte (I)

Charlotte (6)

Miami-Dade (I)

Miami-Dade (6)

Milwaukee (I)

Milwaukee (6)

Omaha (6)

Omaha (12)

219

172

403

254

530

457

335

317

52

77

72

75

126

212

202

221

0.237

0.448

0.179

0.295

0.238

0.464

0.603

0.697

7

6

30

33

91

81

115

111

45

71

42

42

35

131

87

110

0.135

0.078

0.417

0.440

0.722

0.382

0.569

0.502

0.067

0.037

0.309

0.333

0.646

0.319

0.500

0.436

0.253

0.160

0.532

0.552

0.799

0.449

0.635

0.567

Notes:

(I) = Initial interview

(6) = 6-Month interview

(12) = 12-Month interview

Ni

 = Number of Interviewed Victims With Injury at Presenting Incident

Ni1 = Number of Individuals in Ni

 Victimized Between Presenting Incident and Interview

Ni1/Ni = Proportion of Ni With New Victimization Between Presenting Incident and Interview

nd

 = Number of Victims Reporting No Injury After Presenting Incident (De-escalations)

nd’ = Ni1 - nd (Number of Stable Injury Victims)

d = nd

/Ni1 (De-escalation Parameter)

dL = Lower Bound of 95% Posterior Probability Interval for d

dH = Upper Bound of 95% Posterior Probability Interval for d

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 1

Posterior Distribution of Violent Specialization Parameter - Charlotte SARP Data

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 2

Posterior Distribution of Violent Specialization Parameter - Colorado Springs SARP Data

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 3

Posterior Distribution of Violent Specialization Parameter - Milwaukee SARP Data

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 4

Posterior Distribution of Violent Specialization Parameter in Omaha SARP Data - PrePresenting Incident Arrests Only

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 5

Posterior Distribution of Violent Specialization Parameter in Omaha SARP Data - All 

Arrests Through 12 Months After Presenting Incident

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 6

Full Posterior Distribution of Specialization Parameter by Site

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 7

Escalation Analysis from Initial and Six-Month Interviews - Charlotte SARP Data

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 8

De-escalation Analysis from Initial and Six-Month Interviews - Charlotte SARP Data

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 9

Escalation Analysis from Initial and Six-Month Interviews -Miami-Dade SARP Data

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 10

De-escalation Analysis from Initial and Six-Month Interviews - Miami-Dade SARP Data

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

Escalation Analysis from Initial and Six-Month Interviews -Milwaukee SARP Data

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

De-escalation Analysis from Initial and Six-Month Interviews - Milwaukee SARP Data

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

Escalation Analysis from Six- and Twelve-Month Interviews - Omaha SARP Data

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

De-escalation Analysis from Six- and Twelve-Month Interviews - Omaha SARP Data

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.