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

Department of Justice and prepared the following final report: 

Document Title: Family and Employment Consequences of 

Intimate Partner Violence: A Longitudinal 

Analysis 

Author(s): Laura Dugan; Marybeth J. Mattingly 

Document No.: 209295 

Date Received: March 2005 

Award Number: 2002-IJ-CX-0012 

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. 
FAMILY AND EMPLOYMENT CONSEQUENCES OF INTIMATE PARTNER 

VIOLENCE: A LONGITUDINAL ANALYSIS 

by Laura Dugan and Marybeth J. Mattingly

Final Grant Report submitted to the National Institute of Justice 

2005 

This project was supported by Grant #2002-IJ-CX-0012 awarded by the 

National Institute of Justice, Office of Justice Programs, U.S. 

Department of Justice. Points of view in this document are those of 

the authors and do not necessarily represent the official position or 

policies of the U.S. Department of Justice.

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. 
 

ABSTRACT 

In this report, we examine how being violently victimized by an intimate partner 

influences the chances that a woman divorces or separates and moves; changes 

employment; or is re-assaulted by an intimate partner.1 Previous research suggests that a 

high proportion of divorced women had previously experienced marital violence (see: 

Bowlus and Seitz 2002), and that violent partners interfere with women’s employment. 

Thus, it is crucial to consider the ways intimate partner violence is associated with 

marital dissolution and changes in a woman’s employment trajectory. We also consider 

the ways these consequences are influenced by injuries resulting from the violence and 

by the victim’s self-defensive and help-seeking behaviors during and following the 

assault. Recognizing exposure reduction and retaliation effects as competing predictions, 

we assess whether women who attempt to reduce their exposure to violence are more or 

less likely than other victims of partner violence to be re-victimized. 

Victims’ experiences and characteristics are compared to those of non-victims as 

well as other crime victims. Through these comparisons we assess the extent to which 

intimate partner violence uniquely affects individual lives to determine if certain marital 

and employment outcomes are unique to victims of intimate partner violence. 

 Using the 1996-1999 longitudinally linked files of the National Crime 

Victimization Survey, a nationally representative data set, we are able to examine the 

1

 We combine the transition from married to divorced and married to separation into one category because 

separation is often a precursor to divorce, and we are only looking at changes within a six month period. 

The divorce process usually takes longer. 

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

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

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

-ii- 
impact of intimate partner violence in a way that has heretofore been impossible. This 

research expands the understanding of the ways women are affected by violence over 

time. It also provides insight into the role of victim’s agency, revealing how actions 

taken at the time of assault affect later household and employment consequences, and the 

chances of a repeat assault. 

Results suggest that victims of intimate partner violence are indeed more likely to 

divorce and move out of their homes than are other women (both victims and nonvictims). Additionally, such victims more often transition out of the labor force. Help 

seeking and self-defense are only sometimes influential in these outcomes. Finally, our 

results suggest that self-defense increases the risk of repeat assault while exiting the labor 

force is protective against repeat assault. 

This project has direct policy relevance, as it suggests how exposure to key 

community resources, such as legal and medical services, could affect victims. The 

findings may suggest ways to improve interventions to enhance victims’ opportunities for 

positive life outcomes. Additionally, future research can be better designed to target 

specific intervention points. 

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

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

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

Violence perpetrated against women by their male intimate partners was 

historically considered acceptable practice. Later, although it was not overtly accepted, 

many viewed it as a family matter and it became a hidden taboo. After years of feminist 

activism and cultural changes, partner violence has become a topic on which there is 

much concern and public discourse, including policy debates. Many have attempted to 

document the prevalence of intimate partner violence, and some have examined its 

immediate consequences. Yet, little research addresses the months and years following 

assault. Little is known about how partner violence affects women’s work and 

domesticity. We also know very little about whether intervening authorities or a 

woman’s own actions at the time of assault influence the stability (or instability) of her 

home life, employment patterns, and the risk of more assaults from an intimate partner. 

This project makes a first step toward filling this void. 

This project uses the 1996-1999 National Crime Victimization Survey, a 

nationally representative, longitudinal data set, to compare the labor force, mobility and 

divorce consequences of women victimized by their partners with those for other 

victimized and non-victimized women. Thus, while this research focuses on intimate 

partner violence, it also illustrates the consequences for women who are victimized by 

other perpetrators. By linking responses to key questions over time, we estimate how 

incidents of intimate partner violent victimization relate to important changes in women’s 

lives: 1) residential mobility and/or separation, and 2) employment changes. 

-ivThis 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. 
Despite the interrelationships between the different types of family violence, this 

study is limited in scope to men’s aggression toward their partners. Women’s violence 

toward men should be understood differently than male violence, because it is 

qualitatively different. It is more often perpetrated in self-defense (Kurz 1993; Morse 

1995) and less often results in injury (Straus and Gelles 1990a; Zlotnick, Kohn, Peterson, 

and Pearlstein 1998). Thus, we limit our analyses to women’s victimization. 

Research suggests that the institutions battered women are likely to first 

encounter, the legal and medical systems, have typically been insufficient (or outright 

neglectful). We test whether seeking help through these channels improves the victim’s 

work and family life and reduces the likelihood of a subsequent assault. By gaining 

insight into the consequences of intimate partner violence, we see how men’s physical 

dominance can adversely influence women and families. 

Some limited research has been conducted to examine employment changes 

resulting from partner violence. It generally shows that women’s employment suffers 

following violence perpetrated by an intimate partner ( Byrne, Resnick, Kilpatrick, Best, 

and Saunders 1999; Lloyd 1997; Riger, Ahrens, and Blickenstaff 2000). Additional 

research explores how violence influence changes in household composition. For 

example, Dugan (1999) makes a compelling case to consider residential mobility as a 

response to recent criminal victimization. Her findings show that individuals victimized 

within a mile of to their homes are more likely than others to move. Others have 

examined how employment and marital outcomes may be related to repeat assault. Some 

argue that employment may be a means of escaping violent relationships (Dugan, Nagin, 

and Rosenfeld 1999; Farmer and Tiefenthaler 1997; Rogers 1999a). Others suggest 

-vThis 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. 
ending a marriage as a way of reducing intimate partner assault (Bowlus and Seitz 2002; 

Byrne et al. 1999; Sanchez and Gager 2000). 

These studies are typically plagued by at least one of three primary shortcomings: 

first, they rely upon non-representative samples of women; second, they examine only 

victims of intimate partner violence without comparing them to others (or they neglect to 

distinguish between different types of victimization altogether); and/or third, they 

measure only one point in time, inherently missing important changes that can only be 

measured over time.2 By using the longitudinally linked National Crime Victimization 

Survey (NCVS), we overcome these problems, as the NCVS is a nationally representative 

sample of victims and non-victims. It is constructed from repeated interviews, every six 

months, over a three-year period. 

 Further, the current project expands upon a key premise of previously NIJ funded 

research that states that policies and resources designed to decrease exposure between 

partners in a violent relationship will most effectively reduce the rate at which intimates 

kill their partners (Dugan, Nagin, and Rosenfeld 2003). If this “Exposure Reduction 

Hypothesis” were true, we would expect that women who seek help through the medical 

and police establishments to have reduced chances of subsequent assault. That is if these 

establishments responsibly responded to the victims (i.e., by inquiring about injuries, 

providing referral services, etc.). 

Dugan, et al. (2003) also raise the competing “Retaliation Hypothesis” which 

states that a victim’s help-seeking behavior could actually entice her abuser to retaliate. 

-viThis 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. 
They find empirical support that suggests that women who seek intervention could face 

retaliation, particularly if their exposure to violence is not entirely reduced. In fact, 

several scholars have indicated that men intensify their violence when women attempt to 

exit relationships. (Browne 1987; Ellis 1992; and Mahoney 1991; see also Riger, et al. 

2000). 

 This project addresses three primary research questions (and two secondary 

questions): 

1. Are intimate partner violence victims more likely than other women 

(including victims and nonvictims) to divorce or move out of their home 

within six months of a reported assault? 

• Do injury, self-defense, and help seeking influence the chances that a 

victim divorces or separates, moves alone, or that her household 

moves? 

2. Are intimate partner violence victims more or less likely than other women to 

leave or enter the labor force within six months of a reported assault? 

• Do injury, self-defense, and help seeking affect the likelihood of 

changes in victims’ labor force status? 

3. What factors are associated with reports of repeat assault? 

Data and Methods

We address these questions by using the longitudinal data of the National Crime 

Victimization Survey (NCVS), which is the largest nationally representative data set on 

criminal victimization in the U.S. It is administered to a sample of households by the 

U.S. Census Bureau, and is sponsored by the Bureau of Justice Statistics. Its purpose is to 

2

 The relevant research that accounts for victims and non-victims and uses nationally representative 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. 

 

-vii- 
 

gather information about criminal victimization directly from the victims. Thus, the data 

include incidents not reported to the police. The NCVS is a collection of individual 

interviews conducted with the residents of a sample of roughly 50,000 housing units that 

are interviewed every six months for three years. 

studies only intimate partner homicide. It fails to address what happens in cases that fall short of death. 

To address the first research question, we model household disruption as an 

outcome, which includes marital dissolution and residential mobility. Because disruption 

could appear differently depending on marital status, we estimate models separately for 

those married and those who are not married at the time of the interview. We run 

competing risks models to simultaneously examine the likelihood of four outcomes: the 

woman separates or divorces, she moves out of the household, the entire household 

moves, or no change occurs in the six months following interview (between the current 

time t and time t+1). These models include predictors such as the woman’s victimization 

history, demographic and interview characteristics. 

 It is less straightforward to model the dissolution of relationships for unmarried 

women. The NCVS data provides no information on whether unmarried and unrelated 

persons who live together are also intimately involved. Also, many women reside apart 

from their boyfriends. While not ideal, we model the likelihood that the respondent 

moves (alone or with her household), rather than staying in her home. These models 

include the same predictors found in the married models. 

To address the second research question, we use discrete-time event history 

models to examine the effects of violence on longer-term work-related transitions: entry 

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

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

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

-viii- 
into and exit from the labor force. We limit the sample to include only those women who 

are unemployed at the interview for the entry model and employed at the interview for 

the exit model. Thus, a woman can transition from one model to the next after her 

employment has changed. 

 The secondary research questions for 1 and 2 are addressed by re-analyzing each 

of these models on the sub-set of victims of violence by any perpetrator. In addition to 

the factors from the primary models, we also estimate how these outcomes are influenced 

by the circumstances and behavior that occurred during the incident such as the victim’s 

injuries, self-defense by the victim and her help-seeking behavior. The models also 

control for other important incident characteristics such as weapon use and drug/alcohol 

use by the perpetrator. 

Finally, we address the third research question by modeling violence for all 

women who have already reported at least one incident of intimate partner violence. This 

model includes labor force outcomes, marital dissolution, and incident characteristics as 

independent variables and controls for the demographic and interview characteristics 

included in the above models. Thus, we are able to test whether these exposure reducing 

strategies actually reduce the likelihood of more violence, or whether they increase it. 

Before summarizing the findings, we first note that despite its benefits, the NCVS 

has several limitations. It does not ask respondents about their crime victimization 

histories or any other aspect of their lives prior to survey onset. Thus, all models are 

censored to the beginning of the survey period. This could make victims of partner 

violence appear as non-victims, which would bias our findings for intimate partner 

victimization toward zero. The survey omits some special populations such as homeless 

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
and institutionalized populations. Evidence suggests that some of the institutionalized 

such as those incarcerated or living on military bases experience higher rates of intimate 

partner assault (Dugan and Castro 2004; Heyman and Neidig 1999; Richie 1996). 

Without these victims we cannot assess their outcomes making our sample less

victimized than a truly representative sample. Additionally, the NCVS likely includes a 

broad distribution of violence that include domestic disputes that not threatening to either 

partner. On the other extreme are the rarer cases of severe violence that could turn lethal 

because the former is more common than the latter, the NCVS sample likely overrepresents non-threatening violence, diluting our results toward zero. Also potentially 

contributing to this bias is underreporting: some victims will not disclose their assaults on 

national surveys and thus appear as nonvictims. Finally, since the NCVS only interviews 

respondents who live at the sampled addresses, we are unable to assess employment 

outcomes and the risk of subsequent assault for those who move from the sampled 

addresses. 

Results

 The answer to our first research question is a resounding “yes.” Married victims 

of intimate partner violence appear to be more likely than other married women to 

divorce or experience household moves. Unmarried partner violence victims are more 

likely than other women to move. Additionally, they are more likely to move than are 

other violent crime victims. However, the only evidence that a violent crime victim’s 

actions during an assault influence domestic outcomes is with unmarried victims. 

Unmarried victim’s self-defensive actions are slightly related to a higher likelihood that 

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. 

-x- 
they move. Additionally, their calls to the police following an intimate assault are 

associated with marginally lower odds of moving. 

 Our findings addressing the second research question suggest that crime 

victimization is indeed associated with a woman’s entry into the labor force. However, 

investigating all women, we find victims of intimate partner violence have patterns that 

look more like those of non-victims than those of other victims. Yet, when analyses are 

restricted to victims of violent crime, recent intimate partner victimization does, indeed, 

show up as a risk factor for entering the labor force. Thus, it appears when compared to 

all who were violently victimized, those whose assaults were perpetrated by a partner are 

the most likely victims to seek employment after an assault. This is not surprising, given 

that they may need to find work as part of a strategy for becoming more independent of a 

violent partner. Few incident characteristics are associated with entering the labor force. 

The important exception is having been injured to the extent that medical care was 

sought. Both seeking medical help and entering the labor force may represent a victim’s 

agency toward ending the violence. These models also revealed that demographic 

characteristics are less important in predicting victim’s labor force entries than they are 

for the total sample of all women. 

 The findings for labor force exits reveal that victimization history has little 

influence on an employed woman’s odds of leaving work. Additionally, we find a 

violent crime victim’s experiences and actions at the time of assault do not matter. 

 Finally, in response to our third research question, we find important associations 

between an intimate partner violence victim’s responses to assault and her likelihood of 

being re-victimized by an intimate. Actions taken in self-defense appear to increase the 

-xiThis 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. 
risk of sustaining a later assault, while exiting the labor force decreases those odds. Also, 

we find that a victim’s own help-seeking behavior seems to have no effect on her chances 

of re-victimization, yet when others call the police and/or when arrests are made future 

violence appears to be deterred. 

 Our analyses offer more straightforward support for the hypothesis of 

“retaliation” than for “exposure reduction,” since self-defense seems to lead to more, not 

less, violence. However, when someone other than the victim initiates the reduction in 

exposure, such as when another calls the police or when the police make an arrest, the 

“exposure reduction” hypothesis is supported. 

 In sum, our findings do suggest that violent crime victimization and intimate 

partner violence, specifically, are important predictors of changes in household 

composition and employment status. While our findings are not surprising, they provide 

empirical documentation previously unavailable. Further research is needed to examine 

the mechanisms behind these changes and to consider the full nature and history of 

intimate partner victimization. We need to conduct studies that follow a nationally 

representative sample of women, even if they move, in order to track the longer-term 

consequences of violence. 

 While our results provide no cut and dry policy recommendations, they do 

suggest important roles for the police and medical establishments. Had these institutions 

been administering effective intervention to protect women from their violent partners 

and help improve their lives, we would have found consistent significant patterns of 

effectiveness throughout all models. 

-xiiThis 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. 
FAMILY AND EMPLOYMENT CONSEQUENCES OF INTIMATE PARTNER 

VIOLENCE: A LONGITUDINAL ANALYSIS 

INTRODUCTION 

Violence against women by their male intimate partners has gone from acceptable 

practice to a hidden taboo, to a topic on which there is much public discourse, policy and 

concern. Yet, little is known about its affects upon women’s work and family lives. 

Many have attempted to document the prevalence of intimate partner violence, and some 

have examined the short-term consequences. However, with the exception of homicide 

studies (the most extreme consequence), little research addresses the months and years 

following assault. We know very little about the role played by intervening authorities or 

how a woman’s own actions at the time of assault influence her likelihood of divorce or 

residential mobility, labor force trajectory and the risk of subsequent assault. This project 

makes a first step toward filling this void. 

Research Findings on the Extent and Nature of Intimate Partner Violence

 Table 1 describes previous studies that have examined the prevalence of intimate 

partner violence using nationally representative data. It shows information on the sample, 

the time frame, the study design/methods and the prevalence rates. Klaus and Rand 

(1984) found very low rates in the 1973-1981 waves of the National Crime Survey. 

Several factors are cited as reasons. For instance, the context of a crime survey makes it 

unlikely that incidents not normally considered criminal are reported. Interview privacy, 

though desired, was not always attainable; and shame may prevent many from disclosing 

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. 

-1-
their experiences. It is also worth noting that this study took place prior to the redesign 

which added better probes about assaults by an intimate (see Bachman and Taylor 1994). 

Rennison (2003) computed more current rates using the redesigned National Crime 

Victimization Survey (NCVS). The 2001 NCVS rates are presented in Table 1. 

Although these rates are much higher than those found by Klaus and Rand, they are still 

substantially lower than those found by other surveys. Note, however, that these studies 

did not link a woman’s interviews to assess victimization over the entire three year 

interview period. Rather, all of the interviews in a twelve-month period were analyzed. 

Hence, the rates represent a snapshot of victimization in a fairly narrow window and 

often include two interviews with the same respondent. As a hypothetical example, let us 

assume that an interview period had only one woman who was interviewed twice. If she 

only reported intimate partner victimization at one of her interviews, the other interview 

would appear to be reported by a non-victim (despite her victimization within the year 

surrounding that interview), inflating the proportion of non-victims from zero to 0.5. 

Alternatively, if that woman reported victimizations during both interviews in the twelvemonth period, she would be counted twice, but the proportion of victims would remain at 

one. In general, because it is highly unlikely that a woman reports being victimized 

during each interview, the actual proportion of women who were victimized will be 

higher than the proportion of interviews in which the respondent discloses an incident. 

Finally, these rates were computed using bounded NCVS interviews. That means that 

respondents had a concrete reference to the previous interview and were less likely to 

report on incidents prior to the 6-month window inquired about (ICPSR) Thus, it is not 

surprising that the rates are lower than those found in other, unbounded surveys. 

-2-

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
[Table 1 About Here] 

Morse (1995) analyzed data from four waves of the National Youth Survey. Her 

results for heterosexual married or cohabiting couples indicate high prevalence of 

intimate partner assault within the past year: ranging from a rate of 54.5% of couples 

when respondents were between 18-24 years old (and a smaller proportion were in 

married/cohabiting relationships) to 32.4% by the time respondents reached their late 

twenties to early thirties. Morse attributes this change (as well as the discrepancy between 

the rates she found and rates from other studies) to the age range of the sample, varying 

from one at which violence peaks to one at the start of its decline. Morse found that rates 

for severe violence were drastically lower, ranging from 25.5% in the first wave analyzed 

to 15.8% in the last wave (Data Not Shown in Table 1). In the Morse data, rates of any 

female perpetrated violence and of severe female perpetrated violence were higher than 

those of male perpetrated violence across the years. However, as discussed below, Morse 

(1995) carefully addresses gender differences in the nature, context and consequences of 

assault. 

Straus, Gelles and Steinmetz found that in 1975, 16% of all married/cohabiting 

couples in the National Family Violence Survey (NFVS) reported one or more assaults 

during the year (Straus et al. 1990b). In a 1985 follow up study, the rate was similar at 

15.8%. Straus and Gelles (Straus and Gelles 1990a) claim that partner violence is 

underreported and conclude that their numbers represent a lower bound on actual 

incidence of assault. 

 Despite this claim, Straus and Gelles (1990a) find higher rates of intimate partner 

violence than do other researchers (see Table 1). However, their numbers are not directly 

-3-

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

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

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

comparable because they refer only to those currently residing with an intimate partner, 

the group most “at risk” of intimate partner assault. 

 Tjaden and Thoennes (2000b) used similar survey techniques to examine the 

prevalence of intimate partner assault among all adults. They found much lower rates, 

1.5% of women and 0.9% of men reported violent victimization by an intimate in the past 

year. When analyses were restricted to married/cohabiting couples of the opposite sex 

(Tjaden and Thoennes 2000a:151), findings remained similar: 1.4% of women and 0.8% 

of men “reported being raped, physically assaulted, and/or stalked by a current or former 

marital/opposite-sex cohabiting partner in the 12 months preceding the survey.” Tjaden 

and Thoennes (2000a) discuss how their findings differ from those of Straus and Gelles 

(1990a) and highlight the possibility that differences in survey presentation and analytic 

categorization explain the differential rates found in each study.3 Additionally, Tjaden 

and Thoennes use a modified version of the Conflict Tactics Scale employed by Straus 

and Gelles, as well as other survey instruments. 

 Lower rates are also found by Zlotnick, et al. (1998), who studied married and 

cohabiting couples in the National Survey on Families and Households (NSFH), 

suggesting that Straus and Gelles (1990a) have relatively unique findings and that actual 

rates are either much lower or people are generally far more reticent about this topic. The 

3

 If a male or female respondent reports a victimization in the National Family Violence Resurvey, it is also 

counted as a perpetration for the opposite sex when rates are tabulated in Straus and Gelles’ analyses 

(Tjaden and Thoennes 2000a). However, given findings that men and women report differently (see, for 

example:Bohannon et al. 1995), it may not be valid to combine these reports, as doing so may inflate 

estimates. This would partially explain why Straus and Gelles (1990a) find much higher prevalence rates 

among married and cohabiting couples than do other researchers. 

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. 

-4-
context or presentation of the Straus and Gelles (1990a) survey may have invited greater 

disclosure. 

Regardless of which study is considered, there is no doubt that intimate partner 

violence against women remains a pervasive and persistent social problem. Not only do 

those victimized by an intimate (rather than by a stranger) more often tend to experience 

repeated violence by the same perpetrator, but, also, intimate partner violence has 

declined at a slower rate than other types of violence ( see: Rennison and Welchans 2000; 

Rennison 1999). Further, it is likely that societal factors are complicit in maintaining the 

problem. It is therefore essential for social scientists to pursue the issue. In addition to 

its prevalence, spousal violence often implies underlying family dysfunction and is often 

an indicator of other types of family violence (McCloskey, Figueredo and Koss 1995: 

1241, 1256). For example, "fathers who batter their wives are more likely to hurt their 

children" (McCloskey et al. 1995: 1256). McCloskey et al. found that children from 

violent homes are at greater risk both within and outside the family. Specifically, those 

with fathers that battered their mothers were more likely to be incestuously abused 

(McCloskey et al. 1995: 1246). Analyzing woman battering is essential so that proper 

intervention and prevention policies can be established to protect the victimized women 

and their children and to improve the welfare of families. 

Research Agenda

This project uses a nationally representative, longitudinal data set to compare the 

labor force, mobility and divorce consequences for women victimized by their partners 

with those for other victimized and non-victimized women. Thus, while this research 

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. 

-5-
focuses on intimate partner violence, it also illustrates the consequences for women who 

are victimized by non-intimates. By linking responses to key questions over time, we 

estimate how incidents of intimate partner violence relate to important changes in 

women’s lives: 1) residential mobility and/or separation, and 2) employment changes. 

Figure 1 illustrates the main relationships we test. We examine how intimate partner 

violence (A) leads to household disruption and employment consequences (B). We 

additionally consider how these outcomes are affected by women’s injuries and helpseeking behavior at the time of the incident (C). Finally, we address how intimate partner 

violence victims’ characteristics and family and employment consequences affect the 

likelihood of a subsequent act of partner violence (D). 

[Figure 1 About Here] 

Relevant Research Findings

Focus on Intimate Partner Violence Against Women 

Despite the interrelationships between the different types of family violence, this 

study is limited in scope to men’s aggression toward their female partners. Women’s 

violence toward men should be understood differently than male violence, as women’s 

aggression toward men is qualitatively different than men’s violence against women. 

Although some find similar rates of perpetration by men and women or higher 

rates of female perpetration (see, for example: Moffitt, Caspi, Rutter, and Silva 2001; 

Morse 1995; Straus and Gelles 1990a), not all research supports the finding that men and 

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. 

-6-
 

women engage in violence similarly.4

 Tjaden and Thoennes (2000a), using the National 

Violence Against Women Survey conducted in 1995-1996, find that women were more 

likely than men to report having experienced rape, physical assault, and stalking by a 

husband or opposite sex cohabiting partner. They also find differential rates of help 

seeking. Women reporting that they were physically assaulted were more likely than men 

to “report that they had been injured, received medical treatment, received mental health 

counseling, lost time from work, and sought justice-system interventions as a result of 

their most recent victimization” (Tjaden and Thoennes 2000a:155). 

Even in cases where women are aggressive towards their intimate partners, 

research suggests women are more likely to act in self-defense (see Kurz 1993:258), if 

not in response to direct physical threat (perhaps in reaction to emotional assault). 

Additionally, women are more likely to experience physical injury as a result of spousal 

violence than are men, a finding supported by the National Family Violence Resurvey 

(Straus and Gelles 1990a). Using the National Survey of Families and Households, Brush 

(1990:63) finds that although men and women were about equally likely to engage in 

violence, when women were aggressive toward their husbands they “were more likely 

than men to report that they were injured in the course of disagreements with their 

partners” (see also Zlotnick et al. 1998). Morse (1995) found that both women and men 

were more likely to report that either both partners or men, rather than women, initiated 

4

 There is an interesting debate in the literature regarding women’s violence toward their male intimates. 

Moffit et al. (2001) argue that women’s violence may be more easily forgotten by men and thus less often 

reported than is male violence unless specific probes are included in the survey. This could explain why 

some studies show higher rates of male perpetrated assault. On the other hand, Morse (1995) contends that 

women’s violence goes against the role expectations for women and so even minor aggression is likely to 

be remembered as violence, thus inflating the rates of female perpetrated violence in some surveys. 

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. 

-7-
 

fights among couples who reported violence. This suggests that perhaps women, more 

often than men, were acting in self-defense. Further, she found that women who had been 

abused were more likely than men to live in fear of their partner. Also, women were 

more likely to incur injuries from their partner’s violence than were men. Note, however, 

that some research does challenge this claim. Specifically, work done by Moffitt, et al. 

(2001) on the Dunedin Longitudinal Study out of New Zealand finds very high rates of 

both male and female violence and suggests that women do respond violently to male 

violence, but that an antisocial history is also predictive of female (and male) violence net 

of their partner’s violence. Further, factors such as individual attitudes toward aggression 

and involvement in other crime are predictive of violence. Thus there is some evidence 

that self defense is not the only explanatory factor in female perpetrated violence. 

In sum, because of the greater likelihood that women’s violence is perpetuated in 

self-defense and because of women’s greater chance of experiencing an injury at their 

partner’s hand, men’s violence against their female intimate partners is different than 

women’s violence against male intimates. It would thus be unwise to analyze male and 

female perpetrated assaults within the same framework and so our scope is limited to 

violence perpetrated against women. History and culture have allowed and even 

encouraged the violent victimization of women by their male partners and continued 

gendered inequities enable men to continue assaulting the women in their lives.5

5

 For an opposing viewpoint, see Felson (2002). 

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. 

-8-
 

The Criminological and Societal Response to Intimate Partner Violence 

 America is characterized by persistent gender inequality. Violence is but one 

means some men use to control women and maintain their dominance (see: Schecter 

1982). For example, Van Natta (2001) views the normative gender system as a factor in 

all types of intimate violence since it sets the stage for inequitable power dynamics. She 

elaborates that ending domestic violence is linked to adjusting unequal power 

relationships: “As long as individuals are unable to obtain the means to live, some of us 

will be profoundly vulnerable to abuse, we will have few options to escape violence if we 

are victimized, and we will be more likely to be oppressed as human property” (Van 

Natta 2001:32). Empirically, Felson and Messner (2000) found that violent husbands are 

more likely to use threats to control their wives than are other perpetrators of violence--

including female perpetrators of violence against their male partners. They suggest this as 

evidence of the husbands’ attempts at controlling their wives. 

 While male violence against intimates represents one extreme of male control, it 

is both a result and indicator of a society that supports women’s lesser status. This is 

echoed by Morse (1995), who found that women who had been abused were more likely 

than such men to live in fear of their partner. 

 Feminists typically see spousal violence as an expression of the inequality that 

exists between men and women. They believe that violence is used as an instrument of 

male control over women and that it will continue so long as women maintain a lower 

status within society (Kurz 1993: 253, 257-261).6

 Further, "feminist researchers point out 

6

 An alternative hypothesis is retaliation. There is some evidence that as women’s status increases at the 

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. 

-9-
 

that both historically and recently, major institutions have permitted and condoned the 

use of physical abuse by husbands to control wives" (Kurz 1993:259). There is abundant 

evidence that the state has often supported or overlooked spousal abuse. Sheffield’s 

(1999:55) discussion of sentences imposed on male batterers illustrates how attitudes 

infringe upon judicial decisions: 

macro-level, so does the rate at which women are killed by their intimates (Dugan et al. 1999:205). 

In 1981 a Kansas judge suspended the fine of a convicted assailant on the 

condition that he buy his wife a box of candy. In 1984 a Colorado judge sentenced 

a man to two years on work release for fatally shooting his wife five times in the 

face. Although the sentence was less than the minimum required by law, the judge 

found that the wife had “provoked” her husband by leaving him. In 1987 a 

Massachusetts trial judge scolded a battered woman for wasting his time with her 

request for a protective order. If she and her husband wanted to “gnaw” on each 

other, “fine,” but they “shouldn’t do it at taxpayers’ expense.” The husband later 

killed his wife, and taxpayers paid for a murder trial. 

In the first two examples, the severity of a male’s perpetrated violence against his wife is 

minimized by the justice system that is supposed to protect. In the last example, a judge 

dismisses a woman’s concerns for her safety at home, implicitly supporting her 

husband’s right to assault her. Ford’s (1983) work on Marion County, Indiana suggests 

there were systematic problems within the criminal justice system including a lack of 

consistency in cases involving battered women. They could not rely upon the criminal 

justice system for protection. 

 While dramatic changes have since taken place within the criminal justice system, 

many women are still not receiving the help and support that they need. Further, women 

are still being revictimized by the men from whom they have sought protection. A severe 

recent example occurred in March of 2002. A woman in Maryland was killed by her 

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. 

-10-
partner “24 hours after second-degree assault and threatened arson charges against him 

were dropped when he promised in County District Court that he would stay away from 

his wife” (Family Violence Prevention Fund 2003). In this case, the offender had a 

history of domestic assault. Hence, feminists implicate a society that condones and 

accepts violence in the problems of spousal abuse. 

 While male violence against intimates represents one extreme of male control, it 

is both a result and indicator of a society that supports women’s lesser status. Cultural 

factors implicitly (and sometimes explicitly) promote men’s use of violence. For 

example, Crenshaw (1993) links the ways women of color are represented in the media to 

how they are often perceived: violent portrayals legitimize violence against women. 

There is also empirical evidence supporting the idea that violence in the media may 

increase men’s acceptance of violence against women. Malamuth and Check (1981) 

showed that exposure to films showing positive consequences of violence against women 

increased men’s acceptance of such violence. 

 Research suggests that the institutions battered women are likely to first 

encounter, the legal and medical systems, have typically been insufficient (or outright 

neglectful). We seek to better understand whether seeking help through these channels 

improves the victim’s work and family life and reduces the likelihood of a subsequent 

assault. Further, by understanding the consequences of intimate partner violence, we will 

show how men’s physical dominance can adversely influence women and families. 

-11-

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

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

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

Little research has addressed the consequences of intimate partner violence 

experienced by women. Exceptions are studies of injury (see Brush 1990; Dobash, 

Dobash, Wilson, and Daly 1992; Morse 1995; Tjaden and Thoennes 2000a; Zlotnick et 

al. 1998), and the long-term effects of violence on mental health (i.e. Gleason 1993; 

Saunders 1994). Past research on injury has typically used injury as a dependent variable 

to show how men and women suffer differently from intimate partner violence. These 

studies firmly establish that women, more than men are likely to be hurt. While this 

research justifies analyzing women and men separately, it stops short of considering the 

consequences injuries have on women’s lives (e.g. effects upon employment). To our 

knowledge no current research investigates how sustaining an injury impacts the 

likelihood of being revictimized by one’s partner. 

Earlier research on help seeking behavior has examined the problematic nature of 

the medical and legal services encountered by victims. The medical system has 

historically treated women’s injuries without intervening or identifying women 

experiencing intimate partner violence and the legal system does not always offer desired 

protection and intervention (see: Dworkin, 1993; Martin, 1995; Stark, Flitcraft, and 

Frazier 1979; Warshaw, 1993). 

 Similarly, limited research examines family and employment changes resulting 

from partner violence. Existing studies are typically plagued by at least one of three 

primary shortcomings: first, they rely upon non-representative samples of women (or fail 

to distinguish between different types of victimization); second, they examine only 

victims of intimate partner violence without a comparison group; and/or third, they 

-12-

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

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

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

measure only one point in time.7

 By using the longitudinally linked National Crime 

Victimization Survey (NCVS), we overcome these problems, as the NCVS is a nationally 

representative sample of victims and non-victims. It is constructed from repeated 

interviews, every six months, over a three-year period. Below we describe the relevant 

research and discuss its limitations. 

Employment Outcomes 

Within the sociological literature, there is a large body of research on women’s 

employment, the gendered nature of the labor market, and the effects of female 

employment on the family. Research efforts include examining the gender wage gap (see, 

for example: Blau and Kahn 1992) and considering the nature and extent of occupational 

sex segregation and the “glass ceiling” (see, for example: Cotter, DeFiore, Hermsen, 

Kowaleski, and Vanneman 1997; Jacobs 1989; Petersen and Morgan 1995). Others have 

evaluated maternal labor force participation, including the wage penalty of motherhood 

(see, for example: Bianchi 2000; Budig and England 2001; Klerman and Leibowitz 

1999); and studied the division of household labor as women’s time is increasingly 

devoted to market work (see, for example: Bianchi, Milkie, Sayer, and Robinson 2000) 

(Brines 1994; Lennon and Rosenfield 1994; South and Spitze 1994). Some have 

examined the role of female labor force participation in expanding women’s autonomy 

and power within the household (see, for example: Blumstein and Schwartz 1991). As 

Blau, Ferber and Winkler (1998), for example, recognize, economic dependency within 

7

 The relevant research that accounts for victims and non-victims and uses nationally representative data 

studies only intimate partner homicide, but does not address what happens in cases that do not end in 

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. 

-13-
 

marriage often means divorce is not a viable option for women. This research is most 

relevant to our current project. 

death. 

 While we do not compare women’s and men’s labor force experiences, we 

address women’s labor force responses to incidents of intimate partner violence and 

consider how entrances or exits from the labor force influence the risk of subsequent 

assault. Further, we explore how women’s employment trajectories are influenced by 

their own actions at the time of assault and how their employment influences their 

likelihood of subsequent assault. 

 Some scholars have linked violent victimization to negative employment 

outcomes. For example, Lloyd (1997) examined the effects of intimate partner violence 

on women’s employment and found that rather than curtailing employment, women 

experience downward occupational mobility. Her work shows the importance of 

considering consequences beyond the short-term losses in days of work and pay after a 

violent incident. She concludes that intimate partner violence is associated with a higher 

likelihood of unemployment, more jobs (of shorter duration), and more health problems. 

 Lloyd (1997:157) also found evidence that violent partners often played a role in 

women’s employment outcomes: "Some women detailed men’s attempts to influence 

whether they worked, and recounted their partners’ efforts to control and intimidate 

them.” 

 Similarly, Riger t al. (2000) found that women whose partners attempted to 

prevent them from going to work were more likely to quit or lose their job. Also women 

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. 

-14-
whose partners interfered with their participation at work were more likely to miss 

workdays. Forty-six percent of the women in their sample were explicitly forbidden to 

work by the abuser (although the vast majority of these women did work). Eighty-five 

percent of the employed women missed work because of intimate partner violence or 

psychological abuse and 52% had to quit or were fired because of it (Riger et al. 

2000:167). 

 Lloyd’s (1997) sample was not nationally representative, but rather a random 

sample of mostly lower income women in the Chicago area. Thus, it is unclear whether 

the same effects can be generalized to women at higher income levels (who may have 

more resources to exit violent relationships). Her analysis is also limited to bivariate 

associations making it difficult to conclude that the abuse “caused” work displacement. 

The Riger, et al. (2000) study is similarly limited, as it focuses only on shelter residents 

in the Chicago area. It is likely that victims who are not in shelters have different 

experiences than those in the shelter population and there may be geographical variations. 

Byrne, Resnick, Kilpatrick, Best, and Saunders (Byrne et al. 1999) also found 

evidence that violent victimization may negatively influence a woman’s career trajectory. 

They (1999:364) examined changes in women’s employment status after a violent crime 

and found that “women who experienced a new assault were more likely to be 

unemployed than women who did not experience a new assault.” This is suggestive of a 

link between victimization and exit from the labor force; however, their analysis only 

considers movement from being employed to unemployed and does not examine other 

changes in labor force participation. It is also limited by the aggregation of violent crime 

by all offenders. Others research also suggests a linkage between violent intimate partner 

-15-

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
victimization and labor force participation. Using nationally representative data from 

Canada, Bowlus and Seitz (2002) found that women previously victimized by an intimate 

were less likely to be employed; yet, they do not find evidence of a direct link between 

employment and abuse and suggest the difference is because of other differences between 

victimized and nonvictimized women (i.e., nonvictimized women tend to be better 

educated). 

Dugan et al.’s (1999) premise that female victims seek employment to finance the 

departure from violent relationships suggests an alternative hypothesis. This research 

supports the possibility that violent victimization could actually enhance a woman’s 

commitment to the labor force. Victims may seek employment after the onset of violence, 

as a means to gain independence from an abusive partner. Suggestive evidence is 

provided by Rogers’ (1999b) analysis of nationally representative 1980 and 1988 

longitudinal data which suggests that increased marital discord (measured through three 

items including marital instability, relationship problems and marital conflict) increases 

the likelihood that unemployed wives will enter the labor force. Even if abused women 

stay in the relationship, such resources could provide them with greater bargaining 

power. Indeed, Farmer and Tiefenthaler’s (1997) findings suggest that increased income 

decreases violence experienced by women in abusive relationships. 

Other scholars reverse the order of causality, examining how female labor force 

participation may affect violent victimization. Parker and Toth (1990) found that states 

with higher rates of female labor force participation also have higher rates of intimates 

killing one another, suggesting that women’s employment may increase partner violence. 

However, their analysis is not at the individual level and they rely on cross-sectional data 

-16-

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. 
 

possibly confounding the direction of causality. Without knowing the temporal ordering 

of events, they cannot assess whether intimate partner violence induces women to work 

more often to escape their partner, or whether women are killed because they work. 

Other studies found that the role women’s employment played in her chances of 

being victimized by her partner is related to her partner’s work status. MacMillan and 

Gartner (MacMillan and Gartner 1999) show that women’s employment lowered their 

risk when their partners were also employed, but increased her their risk when their 

partners were unemployed. 

Marital Dissolution 

 Research evidence suggests that across time and place, women have used divorce 

as a nonviolent means of ending threatening relationships (Erchak and Rosenfeld 1994; 

Gillis 1996; Levinson 1996). Sievens (2003) found that women in violent marriages 

faced great obstacles in obtaining divorce in colonial America even as laws were 

changing to allow such marital dissolution at the woman’s request. As divorce becomes 

more prevalent and socially acceptable, it is likely that this option becomes increasingly 

viable in the eyes of victims. Despite the increased availability and acceptance of divorce, 

many women today opt to stay in violent marriages, often because they are dependent 

upon their abuser.8

 Indeed, Bowlus and Seitz (2002) found that the likelihood of divorce 

was substantially higher in violent marriages than nonviolent marriages (74% of 

marriages with high severity abuse, 30% of marriages with low severity abuse and 14% 

8

 It is important to note, as well, that exiting a violent marriage does not necessarily end the violence 

perpetrated by the husband (Browne 1995; see: Sev'er 1997). 

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. 

-17-
of nonabusive marriage) ended in divorce. Further, they found that spouses in violent 

marriages have very different characteristics than those in nonviolent marriages and are 

much more likely to divorce. They also found that women with higher educational 

attainment and without children are both more likely to work and more likely to divorce, 

suggesting the importance of constraints and opportunities. 

Sanchez and Gager (2000) also found that nonviolence is associated with lower 

odds of marital dissolution in their study of the National Survey of Families and 

Households. (see, also: DeMaris 2001) This suggests that violence is associated with 

divorce. 

Zlotnick et al. (1998) use the National Survey of Families and Households 

(NSFH) to show that unmarried, cohabiting couples are more likely to have been 

physically victimized than are married couples. This could suggest that violent cohabiters 

are less likely to transition into marriage. Perhaps as more violent marriages dissolve, the 

pool of potential dating partners includes more violent individuals. This is suggested by 

Dugan, et al. (1999:192), who discuss the possibility that declines in the rate of first 

marriage may be linked to “greater selectivity among would-be spouses.” 

One of the few studies that directly addresses marital dissolution following 

intimate partner violence found a positive relationship. Using the three waves of the 

National Women’s Study, a national study that included an oversample of women aged 

18 to 34, Byrne, et al. (1999) found that those women experiencing rape or physical 

assault were more likely than their peers to divorce between the first and third waves of 

the survey. This study is only suggestive because it combines violent victimization by 

intimate partners with other types of violent events. Thus, caution must be taken before 

-18-

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
drawing conclusions about the effects of marital violence on marital dissolution. Further, 

the study only examines bivariate relationships and therefore fails to control for important 

demographic characteristics that could be related to both violence and separation. 

Residential Mobility 

There are several possible reasons why a victimized woman would choose to 

leave her home. Most directly, a woman may move if she is being violently victimized in 

her home. Or, perhaps the entire family may relocate to protect a daughter from a violent 

boyfriend. Additionally, if a marriage dissolves, both partners may be forced to move 

since the marital household could be too costly for either to maintain independently. Few 

scholars have addressed the role of intimate partner violence in women’s residential 

mobility decisions. By considering this outcome, we hope to better understand some of 

the complex factors that may result in a move. We recognize that intimate partner 

violence is only one of a nexus of factors associated with mobility. Victims may move for 

other reasons (even to stay with an abusive partner who needs to move for a job). 

Dugan (1999) makes a compelling case to consider residential mobility as a 

response to recent criminal victimization. Her findings show that individuals victimized 

within a mile of to their homes are more likely to move than others. However, these 

findings are not generalizable to victims of partner violence as her study intentionally 

excludes those cases. Further, since she investigated household moves instead of 

individual moves, her methods failed to detect victims who moved while the rest of the 

household remained. In this project, we explicitly examine individual moves and 

compare victims of intimate partner violence to other crime victims. It is likely that the 

-19-

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. 
moving decisions of victims of intimate partner violence are very different, given the 

danger within rather than outside of the home and their inter-dependence with the 

perpetrator. 

Intervening Factors 

We also explore the roles of injury, self-defensive actions at the time of assault 

and contact with the legal and medical systems immediately following assault. In fact, 

these outcomes may influence the relationship between intimate partner violence and 

marital dissolution, residential mobility and employment changes. 

For instance, those with injuries may be more likely to restrict their activity and 

hence become more dependent upon their partners, it is possible that they will suffer 

greater employment consequences and be less likely to separate from their partners. 

Alternatively, the injury can serve as a “wake-up call” leading women to exit the 

relationship. Browne (1987) found that victims of intimate partner violence who killed 

their partners often did so after escalation in violence, to levels that had not been 

experienced before. Injuries may be one level of escalation that pushes some victims to 

leave their partners. 

Prior research on self-defense was conducted within the context of who 

precipitated the violence. Scholars have found that women are more likely than men to 

assault their intimates in response to partner-precipitated violence (see: Kurz 1993; 

Morse 1995). However, the extant research neglects to explore how a woman’s selfdefensive actions influence change in her family, employment, or risk of future assault. 

-20-

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. 
Much research has examined victims’ contact with police and medical 

establishments. Some have evaluated the ability of police and medical establishments to 

detect and intervene in intimate partner violence. For example, Stark, et al. (1979) 

discuss how the medical establishment ‘fails’ battered women. In their study of women at 

a large urban hospital, they found that the battered woman does not fit into the model of 

diagnosable diseases: “...the patient’s persistence, the failure of the cure, and the 

incongruity between her problems and available medical explanations lead the provider 

to label the abused woman in ways that suggest she is personally responsible for her 

victimization” (461). Indeed, the researchers found that many doctors do not even ask 

women how they were injured and whether they have injuries that are not obvious. 

Further, the treatment battered women received for their injuries was often inappropriate. 

Such concerns were echoed in Warshaw’s (1993) research at an urban emergency 

room in a training hospital. She reviewed female charts for a two-week period and 

searched for indications of abuse. The sample includes 52 cases where women were 

obviously purposefully injured. Warshaw found detection and intervention lacking and 

that personnel were not receptive to the special needs of battered women. For example, 

victim’s clues often went ignored and doctors did not tend to elaborate on information 

collected by the nurses. Additionally, in most cases (78%), doctors did not ask about the 

relationship to the perpetrator. Stark et al. (1979) view the system as contributing to the 

problem. They see radical change as essential for advancing women in society and ending 

domestic abuse. Among their ideas are woman-centered networks that empower her in 

times of need. 

-21-

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

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

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

Other scholars have considered how police intervention might affect women 

victimized by intimates. Some recognize inherent biases within the legal system. Ferraro 

(1993) explicitly points to race, class, and sexuality privileges inherent in the legal 

system, and challenges the demonization of individual men rather than considering the 

societal roots of domestic abuse. She critiques the ways in which legal services and 

protections are offered to victims and questions the ways inherent gender, class, 

sexuality, and racial biases may play into the treatment victims receive. 

Another theme is that the legal system does not adequately consider the gendered 

nature of assault. Ferraro (1993) notes that gender-neutral language ignores the 

differential context in which male and female violence tends to take place. She cites 

incidents where women who phoned police wound up being the ones arrested, since 

officers do not always see the gendered nature of family conflicts and notes: “When 

police arrest women for defending themselves against battering, the abusers are provided 

social support for initiating and justifying violence” (169). 

Many express concern that individual victims’ needs are not adequately 

considered. Bowman (1992) critiques making it mandatory for the police to arrest in 

domestic violence cases since there is no evidence that such policies deter future 

violence, or that it is necessarily the response that women want. Ferraro (1993:173) also 

questions the effectiveness of mandatory arrest and prosecution policies and emphasizes 

that “...women are the best experts on their own lives.” She cites evidence that allowing 

victims to drop charges actually decreases recidivism.9

 Bowman emphasizes the 

9

 It is, however, possible that dropping charges reduces the likelihood not of assault, but of reporting assault 

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. 

-22-
 

importance of the entire response to domestic assault, beginning with a call to police and 

extending through prosecution and aid to victims. While she realizes some women may 

find it empowering to have their abusers arrested, others may not want this response, 

favoring a different response from police, and may be reluctant to call the police if they 

fear their spouse will be arrested. Bowman clearly indicates the need for more research 

that considers women’s needs. She ultimately calls for a response that will prosecute 

offenders and provide support for their victims. 

to the police. 

Researchers have specifically addressed the influence of arrest policies on 

intimate partner violence. The most notable are a series of arrest experiments beginning 

with one by Sherman and Berk (Sherman and Berk 1984) who examined spouse assaults 

in Minneapolis. Their findings suggest that arrest was more effective in decreasing the 

prevalence of assault than were either offering advice or ordering the perpetrator away 

for eight hours. This finding influenced policy-makers to institute mandatory arrest 

policies in many jurisdictions. Similarly, Berk and Newton (1985) examine the police 

records of a county in Southern California. Their results also suggest that arrests are 

associated with fewer new incidents of wife assaults, particularly among those most 

likely to be arrested. They cannot determine if this is because assaults go down or 

reporting declines. Further, evidence regarding the effectiveness of arrest is mixed and 

some replication studies found opposite results, particularly when looking at the 

unmarried and unemployed (see, for example: Berk, Campbell, Klap, and Western 1992; 

Pate and Hamilton 1992). However Dugan (2003), using the yearly (not longitudinally 

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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-
linked) files of the NCVS data finds evidence to suggest that laws may actually reduce 

the number of spousal violence assaults (and have little influence on assaults by 

boy/girlfriends). 

Finally, there is empirical evidence that suggests that women victimized by an 

intimate partner have different help-seeking patterns than those assaulted by nonintimates. In her study of the 1993 Canadian Violence Against Women Survey, 

Kaukinen (2002) found that those assaulted by a spouse or cohabiting partner were more 

likely than those victimized by a dating partner, another known offender or a stranger to 

either seek little or no help or to seek substantial help (by telling family and friends and

notifying a formal agency). Such victims were least likely to disclose to personal 

networks alone. Kaukinen’s findings suggest that assault by a spouse or cohabiting 

partner may most often be concealed but “once the process of disclosure is initiated, 

women victimized by spousal offenders may no longer be able to conceal or normalize 

the violent actions of their abuser” (Kaukinen 2002:28-29). 

Repeat Assault 

 One of the most severe consequences a woman may experience following 

intimate partner assault is re-victimization. Johnson’s (1995) categorization of intimate 

partner violence indicates that severe male violence used to control women is linked to 

future assaults escalating in severity. It is important to examine the extent of repeat 

assault given the potential consequences (injury, death) and to identify the factors that 

increase or decrease risk. By linking NCVS respondents over time, we are able to detect 

-24-

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

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

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

subsequent assaults by an intimate.10 

 Previous research using 1978-1982 data from the National Crime Survey found a 

high rate of repeat assault within six months of the first (Langan and Innes 1986). 

Further, 37% of the married, divorced and separated victims who reported the incident to 

police cited concerns about future violence. Lower rates of repeat assault were found by 

Rand and Saltzman (2003) who analyzed recurrent intimate partner violence in the 1992-

1999 NCVS. Most victims (72%) reported only 1 intimate partner victimization in the six 

months prior to interview.11 Note, however, that both of these studies are limited because 

they ignore the repeated interviews of each woman. Thus, for example, if a woman 

reported being victimized during the first interview and then again during the third, their 

findings would report the content of those interviews as victimizations of two different 

women without repeated incidents. By using longitudinally linked files, we are able to 

link women over multiple interviews and capture recurrent victimization over a longer 

period of time. 

 Johnson (2003) analyzed data from a nationally representative sample of 

Canadian women. Her findings “suggest that a continuation of assaults on wives is 

predicted by the frequency of previous assaults, the youth of male perpetrators, living in a 

common-law relationship, the duration of the union [shorter unions imply greater risk], 

and higher education for female victims” (Johnson 2003:75). Further, she found that a 

male partner’s attempts to limit the woman’s access to family income and restrict access 

10 While we are able to detect whether the respondent was once again violently victimized by an intimate, 

we are unable to conclude whether it was the same perpetrator as the initial incident. 

11 Note that series victimizations were counted as only 1 victimization in the Rand and Saltzman study 

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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. 

-25-
 

to social networks elevated the risk of later assault. This might suggest that if a male 

partner wants to limit a woman’s access to income and thus force her to leave the labor 

force, her risk of repeat assault may be elevated. 

(2003). Thus, they inherently under count repeated incidents of violence. 

Competing Hypotheses: Exposure Reduction or Retaliation 

This research expands upon a key premise of previously NIJ funded research that 

states that policies and resources designed to decrease exposure to violent partners will 

most effectively reduce the rate at which intimates kill their partners (Dugan et al. 2003). 

If this “Exposure Reduction Hypothesis” were true, we would expect that women who 

seek help through the medical and police establishments to have reduced chances of 

subsequent assault. That is if these establishments responsibly responded to the victims 

(i.e., by inquiring about injuries, providing referral services, etc.). 

Dugan, et. al (2003) also raise the competing “Retaliation Hypothesis” which 

states that a victim’s help-seeking behavior could actually entice her abuser to retaliate. 

They find empirical support that suggests that women who seek intervention may face 

retaliation, particularly if their exposure to violence is not entirely reduced. Further, 

several scholars have indicated that men intensify their violence when women attempt to 

exit relationships. (Browne 1987, Ellis 1992, and Mahoney 1991, see also Riger et al. 

2000). 

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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-
Research Questions

 Having reviewed the above literature, it becomes immediately apparent that data 

limitations confine our knowledge in this area. The data set we constructed allows us to 

address questions whose answers require information on the same women over time. 

There are three primary research questions that this project addresses: 

1. Are intimate partner violence victims more likely than other women 

(including victims and nonvictims) to divorce or move out of their home 

within six months of a reported assault? 

• Do injury, self-defense, and help seeking influence the chances that a 

victim divorces or separates, moves alone, or that her household 

moves? 

2. Are intimate partner violence victims more or less likely than other women to 

leave or enter the labor force within six months of a reported assault? 

• Do injury, self-defense, and help seeking affect the likelihood of 

changes in victims’ labor force status? 

3. What factors are associated with reports of repeat assault? 

METHODOLOGY 

Data

Although data collection began in 1973, additional probes were added in 1992 to 

elicit responses about violence perpetrated within the family, thus making the survey 

better suited to study intimate partner violence. (For discussion of the redesign, see 

Bachman and Taylor 1994) We use data collected from 1996 to 1999 and linked 

longitudinally by Marshall DeBerry of the Bureau of Justice Statistics. Census Bureau 

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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-
changes in the survey design and sampling procedure preclude construction of a 

longitudinal file prior to 1996 (Bureau of Justice Statistics 2002) and longitudinally 

linked data are not available past 1999. The data include 50,115 women. 

This study uses the longitudinal data of the National Crime Victimization Survey 

(NCVS). The NCVS is the largest nationally representative data set on criminal 

victimization in the U.S. It is administered to a sample of households by the U.S. Census 

Bureau, and is sponsored by the Bureau of Justice Statistics. Its purpose is to gather 

information about criminal victimization directly from the victims. Thus, the data 

include incidents not reported to the police. The NCVS is a collection of individual 

interviews conducted with the residents of a sample of roughly 50,000 housing units that 

are interviewed every six months for three years. The first interview at the housing unit is 

conducted in person, while the follow-up interviews are generally done over the 

telephone. If a household moves, the new occupants of the housing unit are interviewed 

in subsequent waves. That is, the NCVS is a longitudinal sample of housing units rather 

than a longitudinal sample of individuals or households who are followed as they move. 

Because the NCVS is a general crime survey, it is well suited for comparing 

victims of intimate partner violence to victims of other types of crime. The survey gathers 

detailed information on all recent criminal victimizations reported by each household 

member over the age of 12. Because the NCVS provides information about the 

relationship of perpetrator to victim, and the circumstances following the event, it is 

possible to distinguish intimate partner violence and to estimate how the victim’s 

behaviors influence future consequences. Further, by linking the file over time, we are 

-28-

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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. 
able to compare responses from earlier interviews with those in later interviews to 

determine how victimization shapes changes in women’s lives. 

The unit of analysis in the proposed study is the woman. We examine a woman’s 

victimization pattern and the subsequent changes in her life for the period that she is 

followed in the survey (up to three years). We estimate outcome differences between 

victims of intimate partner violence and 1) victims of other violence 2) victims of nonviolent (property) crime, and 3) non-victims (when appropriate). However, the primary 

focus is on the ramifications sustained by victims of intimate partner violence. Appendix 

A details the crimes included under violent and other crimes. Note that we also include 

break-ins and intended forcible entries under intimate partner violence, because these 

crimes represent likely intentions of violence since current and former partners either 

have access or would not be in the home unless they are hoping to assault or harass their 

current or former partner. 

Variables 

Following is an overview of the variables we use in our analyses. For further 

details on survey questions, variable construction, and handling of missing data please 

refer to Appendices B and C. For descriptive statistics, across woman-interviews, on 

each of the variables, see Appendix D. 

Dependent Variables: 

Exiting the Relationship is captured through a series of variables. Divorce is 

measured as a transition from being married to being divorced or separated at the 

following interview (This variable will only be used for interviews where the woman 

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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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-29-
reports being married.) Individual residential mobility represents a move by an individual 

woman since the previous interview, while other members of the household remain at the 

address, which is suggestive of marital dissolution. This is indicated when a household is 

interviewed, but an individual woman is not and it is reported that she has moved. A 

more ambiguous indicator is when the entire household has moved between interview 

period t and interview t+1. A fourth option is that there is no indication of divorce or 

household disruption and it is, therefore, assumed that the marriage remained intact. 

These four categories will be combined into one categorical dependent variable for many 

analyses. A version of the marital dissolution variable is included in a model predicting 

subsequent assault. It refers to a marital dissolution since last interview and is coded (0) 

for those unmarried at t-1. This model also includes a dummy coded variable to indicate a 

missing value on marital dissolution. 

Employment Consequences are captured through several variables. We illustrate 

how when we measure employment for victims and non-victims in Figure 2. If a woman 

was victimized between time t and time t+1, her status change is coded based upon 

whether or not she reported being employed at the time of the first crime incident 

(reported at t+1) and comparing that to whether or not she was employed at time t+1. 

Non-victims are coded according to their employment status at time t and time t+1. We 

use victims’ status at incident because 60 percent of intimate partner violence victims 

were not interviewed prior to their first reported assault, but we have available their 

(retrospective) report of employment status at the time of assault. For those moving from 

being unemployed to being employed we assume entry into the labor force. For those 

employed and later reporting they are unemployed, we code an exit from the labor force. 

-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. 
Both of these variables are included as predictors in a subsequent assault model. Those 

employed at prior interview (nonvictims) or first assault (victims) are coded (0) for the 

entering the labor force variable in these models, while those unemployed are coded (0) 

on leaving the labor force. Missing values on each are coded (0) and missing indicators 

are also included in the model. 

[Figure 2 About Here] 

Subsequent Intimate Partner Violence is an indicator of whether or not a 

subsequent intimate partner assault occurred during the interview period. It is coded (1) 

for any interview period with more than 1 reported assault and for interviews with any 

reported assault after previously reported assault(s). 

Primary Independent Variables:

Recent and previous victimizations capture all reported crime incidents during or 

prior to the current interview. For each interview period, we construct variables to tally 

the number of reported victimizations over the past six months for four types of offenses: 

1) violence perpetrated by an intimate, 2) violence by a known offender, violence by an 

unknown offender, and 4) nonviolent crime (see Appendix A). We construct two 

indicators for each crime type, recent and previous victimization. A recent victimization 

refers to the number of victimizations in the past 6 months reported in the current 

interview. Previous victimization is measured by the average number of victimizations 

reported for the 6 months before each interview prior to the current interview. Figure 3 

provides an example of how each is constructed. The first line shows the actual number 

of reported victimizations. Note that this hypothetical woman was not interviewed 

during time 2. At time 3, recent number of victimizations is 1, the number reported at 

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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. 

-31-
that interview. Her average prior intimate partner victimization is 1 per six months (2 

total prior incidents/2 prior completed interviews). The average number of incidents 

reported at time 0 is set to 0 since there was no prior time point to report. Note that since 

she was not interviewed at time 2, this interview is excluded from analyses. 

 

[Insert Figure 3 About Here] 

 We also constructed an average of intimate partner violence episodes to date. 

This is the average number of intimate partner incidents reported prior to subsequent 

assault. It is constructed the same way as described above, except that if there are no 

previous intimate partner assaults, then we count the first current assault. For most 

models, we use the recent and previous measures of intimate partner assault described 

above. However, we use this variable in the models predicting subsequent assault, as it 

includes information about the first assault reported at interview, if there are no previous 

assaults. Thus, it combines information about assault history and current assault. 

 Sometimes multiple incidents are collected under one incident. These are termed 

series incidents and the NCVS collects information about them collectively. Such 

incidents represent a minimum of 6 incidents of similar type for which a respondent 

cannot recall sufficient information to report on them separately. To be conservative, we 

assign series incidents a value of 6 in the tally of incidents, given the extreme range of 

reported series events. 

Intervening Variables:

Self-Defense during the course of a crime incident is recorded through responses 

to two survey questions: “Did respondent use or threaten to use physical force against the 

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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-
 

offender?” and “Who was the first to use or threaten to use physical force - you, the 

offender, or someone else?” It is coded (1) if the respondent used or threatened physical 

force and the perpetrator was the first to do so during any crime incident prior to 

interview. For the subsequent assault models, this variable is coded (1) for any reported 

use of self-defense during an intimate partner assault prior to a current, subsequent 

assault. Thus, it is coded (1) in cases where self defense was used during an incident 

reported in a prior interview, or if there were no prior assaults, during the first assault 

reported at current interview. 

Injury following violent crime is captured by responses to the survey question: 

“What were the injuries you suffered, if any? Anything else?” asked about all crime 

incidents reported. It is a binary variable coded (1) if a respondent experienced any 

physical injury as a result of violent victimization prior to interview.12 For the subsequent 

assault models, this variable is coded (1) for any reported injury during an intimate 

partner assault prior to a current, subsequent assault. 

Seeking medical attention is a binary variable coded (1) if a woman injured during 

any violent incident reported to date and received medical attention for any of her 

injuries. Victims were asked: “Were you injured to the extent that you received any 

medical care, including self treatment? Where did you receive this care? Care received at 

the scene of the incident or at home/neighbor’s/friend’s is excluded so that this variable 

represents actually seeking help from a medical establishment. This variable is coded (1) 

12 The NCVS does not collect information about psychological trauma or other emotional injury. 

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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. 

-33-
for any reported medical attention for injuries incurred during an intimate partner assault 

prior to a current, subsequent assault for the subsequent assault models. 

Victim notifying the police is an indicator variable coded (1) if a victim reports 

that she contacted the police following at least one victimization during or before the 

interview period.13 For the subsequent assault models, this variable is coded (1) if she 

notified the police after an intimate partner assault prior to a current, subsequent assault. 

Control Variables:

We control for several demographic characteristics. Age is measured in years. 

We assign the age recorded at a woman’s first interview for that interview and increment 

it by 0.5 year (six months) each following interview. 

Race is coded into five indicator variables by examining responses to race and 

Hispanic origin questions on the survey. The five categories available are white, nonHispanic; black, non-Hispanic; Hispanic; Asian, non-Hispanic; and Native American, 

non-Hispanic. Respondents are assigned the race reported during their first interview. 

Missing values are assigned to a separate category, race missing, which will be included 

in regression models. For some of the models with small sample sizes, we combine racial 

groups. White, non-Hispanic is the reference category in multivariate analyses. 

Educational attainment is collected in years and recoded into three categories: 

less than 12 years, 12 years, and more than 12 years. Missing values are assigned the 

value at preceding interview if it matches the value at subsequent interview. Remaining 

missing cases are classified as zero for both education measures and dummy coded as 

13 Note that this variable represents only calls to the police made by victims. We also include a control 

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-34-
 

missing education in the model. High school graduates with no college education are the 

reference group. 

variable indicating police contact by another person in our models run on victims of violent crime. 

 Low-income households include those that report a family income of less than 

$15,000 annually. The second captures the other tail of the distribution. High-income

households are recorded as having family incomes of more than $75,000 annually. 

Women who fail to report their family income during any given interview may have 

reported income in an earlier or later interview. In these cases we assign the average 

reported income across the prior and subsequent interview periods. Remaining missing 

cases are assigned a value of 0 for all of the income variables and recorded as a 1 for a 

dummy variable indicating missing income. 

Marital status is measured by three indicator variables: married, 

divorced/separated, and single (never married or widowed). Those missing on marital 

status are assigned the value reported at the prior interview if that value matches the 

value at the subsequent interview and coded (1) on an imputation flag. This imputation is 

done after the divorce/separation variable is coded so that there is no imputation on that 

dependent variable. An indicator is included for those whose marital status is unknown 

and cannot be determined by the surrounding interviews. 

Indicators are also included to capture whether or not a respondent was employed

during the two weeks prior to interview. Missing values on employment status are 

assigned to (0), if a respondent reported that she had not worked at all in the past six 

months (a separate survey question). Otherwise, those missing information on 

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-35-
employment status are assigned the value at prior interview if it matched the value at next 

interview. Note that the latter imputation is done after the employment change variables 

are constructed so that it does not affect the dependent variables. An indicator is included 

for those whose employment status is unknown and cannot be determined by the 

surrounding interviews. 

Student status is an indicator variable coded (1) if a respondent reports that he/she 

was attending school at the time of interview. Missing values for student status are 

assigned the value at prior interview if it matched the value at next interview. Remaining 

missing cases were assigned (0) and a missing flag was created. 

Tenure is an indicator of the number of months a respondent reports having lived 

at the address. It is calculated by assigning the age recorded at a woman’s first interview 

for that interview and incrementing it by six months each following interview. Missing 

values are assigned the mean value for the sample of all women and an imputation flag is 

created. 

 Home Ownership is coded (1) if a respondent reported that the household owned 

or was in the process of purchasing the home. Missing values are imputed to the value at 

prior interview if it matches the value at subsequent interview. 

Respondents living in multiple unit dwellings during their first interview are 

coded (1) for all interviews. Those in public housing during the first interview are coded 

(1) for all interviews. Missing values on multiple unit and public housing residences are 

coded (0) and missing indicators are constructed. If a residence was considered urban at 

first interview, that value is assigned for all subsequent interviews. 

-36-

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Household composition is captured through three variables. One adult households 

contain only one person over age 12 in the home; two adult households are the omitted 

category; many adult households are comprised of at least three adults; and number of 

children is a count of those under age 12. 

We also control for three interview characteristics. First, we include the 

household’s interview period, which indicates how long the address has been in the 

sample. Second, it is noted whether or not the interview was conducted by proxy, (i.e., 

someone other than the intended respondent). And finally, in models predicting 

subsequent assault, where telescoping bias is likely, we control for the first, unbounded

interview. Five incident characteristics are also included in models run on victims only. 

Police notification is an indicator variable coded (1) if someone other than the victim 

contacted the police following any victimization prior to interview.14 Arrest is coded (1) 

if the respondent reports that she knows of any arrests or charges brought as a result of 

any crime incident prior to interview. Weapon use is coded (1) for affirmative responses 

to the question: “Did the offender have a weapon such as a gun or knife, or something to 

use as a weapon, such as a bottle or wrench?” for any incident occurring prior to 

interview. A perpetrator is considered being under the influence if a victim says s(he) 

was using drugs or alcohol at the time of any assault reported to date of the interview. 

Finally, a series flag is created to indicate if any of the victim’s recent or prior 

14 For the subsequent assault models, these variable are coded (1) for any reported police contact by 

someone else, arrest, weapon use, perpetrator under the influence, and series incident during or following 

an intimate partner assault prior to a current, subsequent assault. 

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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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-37-
victimizations were part of a series incident. In the subsequent assault models, we control 

for one additional characteristic: whether or not the offender did this before. 

Methods 

 In Figure 1, we illustrate the conceptual model for this project. The statistical 

models are designed to assess the ways incidents of intimate partner violence (A) affect 

exiting the relationship (divorce/separation/residential mobility) and employment status 

changes (B). We also consider how intervening variables, including a measure of the 

immediate consequence of intimate partner violence (injury), and measures of women’s 

agency (help seeking behavior) moderate the relationships (C). Finally, we examine how 

the consequences of intimate partner violence (B) relate to the likelihood of repeated 

violence (D). Each of the outcome variables is described below and in Appendix B. 

 Our analyses compare victims of intimate partner violence to four other groups of 

women: 1) victims of violence by a non-intimate, known offender, 2) victims of stranger 

violence, 3) victims of non-violent crimes, and 4) non-victims. Thus, we are able to 

disentangle the effects of a violent victimization by an intimate from those of 

victimization, more generally. Further, because we can link interviews of the same 

woman over time, we can distinguish ongoing patterns of violence from “one-time” 

incidents by examining each woman’s reports of violence across interviews. Our models 

include both a count of current victimizations and an average of prior victimizations. This 

allows us to investigate whether the extent of violence is an important predictive 

dimension across outcomes. 

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-38-
All analyses also consider variations by race/ethnicity and social class and other 

demographic and interview characteristics. In models where we investigate only victims, 

we also control for incident characteristics such as whether a weapon was used. 

We estimate parameters for the dependent variables characterized in Boxes B and 

D of Figure 1. Table 2 lists the dependent variables (outcome), the key predictors, the 

specific sample, and the modeling structure. Following is a brief description of these 

models. Our unit of analysis in all models is the individual woman. 

To address the first research question, we model household disruption which 

includes marital dissolution and residential mobility (Table 2, Models 1 and 2). Because 

disruption could appear differently depending on marital status, we estimate models 

separately for those married and those who are not married at each interview. Model 1 in 

Table 2 shows the specifications for the married respondents. We run competing risks 

models to simultaneously examine the likelihood of four outcomes: the woman separates 

or divorces, she moves out of the household, the entire household moves, or no change 

occurs in the six months following interview (between the current time t and time t+1). 

Thus, the models are actually stacked multinomial logistic regressions with four possible 

outcomes, where each line of data is a woman interview. They include predictors such as 

the woman’s victimization history, demographic descriptions, and interview 

characteristics (as collected at time t). Since we have no information after the survey 

period ends, all models are right censored. 

[Table 2 About Here] 

 The NCVS data provides no information on whether unmarried and unrelated 

persons who live together are also intimately involved. Also, many women reside apart 

-39-

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from their intimate partners. Therefore, it is not possible to accurately predict relationship 

dissolution for unmarried women. Also, since many unmarried women live alone, an 

individual move is also a household move. Thus, for these women we use a stacked 

logistic model to estimate the dichotomous outcome of moving (versus staying in the 

household) during in the six months following an interview. We choose the discrete-time 

model over a continuous model because the specific dates of household disruption are not 

included in the NCVS. Covariates in model 2 are the same as those in model 1. We 

estimate the hazard rate, or conditional probability that a woman moves by time t+1, 

given that she was in the sample in time t. 

To address the second research question, we use discrete-time event history 

models to examine the effects of violence on longer-term work-related transitions: entry 

into and exit from the labor force (Table 2, Models 3 and 4). Since each of these 

outcomes is dichotomous, we estimate the models using logistic. We limit the sample to 

include only those women who are unemployed at the interview for the entry model and 

employed at the interview for the exit model. Thus, a woman can transition from one 

model to the next after her employment has changed. 

As described above and in Figure 2, respondents’ employment status is measured 

at the time of the incident for victims and during interview t for non-victims. Using those 

definitions, entry into the labor force is defined as a transition from being unemployed at 

that measurement to being employed in time t+1. Similarly, exit from the labor force is 

coded when an employed respondent at measurement reports being unemployed at time 

t+1. Also estimated in these models are the impact of a woman’s victimization status and 

demographic and interview characteristics. While most of these variables remain 

-40-

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constant over interview periods, we follow the measuring schema shown in Figure 2. 

Because we only have this data during interview periods (and not at the time of the 

incident) and because 60 percent of all victims were interviewed for the first time after 

their first incident, we measure these other variables for victims and non-victims at time 

t+1. 

We rely on discrete-time event history modeling because the survey excludes the 

dates when employment changed. The data is censored at both ends, since we have no 

information on employment prior to time 0 or after time 6. Hazard models account for 

right censoring and we addressed the nature of error due to left censoring above. 

To address the secondary research questions for 1 and 2, we re-analyzed models 1 

through 4 on the sub-set of violence victims.15 We estimate how the ramifications of 

partner violence are influenced by self-defense, the help-seeking behavior described in 

Appendix C and injuries. The models also controls for important incident characteristics 

that likely influence the outcomes (e.g. weapon use, drug/alcohol use by the perpetrator). 

We compare estimates between victims of intimate partner violence, victims of violence 

perpetrated by another known offender, and victims of stranger violence. 

Finally, to address the third research question, models predicting subsequent 

violence by an intimate (Table 2, Model 5) are estimated for all women reporting at least 

one incident of intimate partner violence.16,17 It is important to note here that the 

15 For analyses of violent crime victims, we include all woman-interviews for crime victims from the time 

of first violent crime victimization on. Thus, a woman reporting her first violent crime victimization at 

time 3 is included from time 3 on even if no further victimization is reported. (Prior to time 3, we have no 

evidence that she is a victim.) 

16 Our subsequent assault models include victims of intimate partner violence from the interview they first 

report an assault until they exit the sample. 

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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. 

-41-
 

perpetrator of the subsequent attack may be different from the earlier offenders. Due to 

data limitations, in most cases, we are unable to verify whether the second partner is the 

same as the first. Thus, we estimate the probably that a victim was violently attacked by 

a partner during the current interview period, provided that the she has already been 

assaulted by a partner (not necessarily the same one) while participating in the survey. 

Since this outcome is dichotomous, we use logistic regression. A subsequent assault is 

also noted, by definition, if a woman reports multiple intimate partner violent 

victimizations during the survey period. Since details are reported for each incident 

(including the date), we are able to discern the characteristics that distinguish the initial 

victimization from the subsequent assault. However, this level of detail is missing if the 

incident is part of a series. Because 8.5 percent of the victims report at least one set of 

series events, we rely on the discrete time event history modeling to predict the likelihood 

that a victim of intimate partner violence was assault again by an intimate within the six 

months prior to interview. An additional model [not shown in Table 2] includes 

divorce/separation and labor force status changes as independent variables to test whether 

these outcomes influence a victim’s likelihood of being violently victimized again by an 

intimate. 

All models in Table 2 are weighted with the person weight provided by the 

Bureau of Justice Statistics. Also, due to competing predictions, all statistical tests are 

two-tailed. 

17 Since these models are restricted to those who report at least one incident of intimate partner violence, 

we do not compare these estimates to those for victims of other crime types or nonvictims. 

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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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-42-
Data Limitations 

Left Censoring

 Since we have very little information about women’s lives prior to the first 

interview, the data is inherently left censored. Thus, women who were victimized only 

before to the survey period began will appear as non-victims in the data. Left censoring 

will never make non-victims appear as victims. Left censoring will likely have its 

greatest impact early in the survey period for women who were victimized just before 

entry. If intimate partner victimization does, indeed, impact marital, moving, or 

employment outcomes, these women will appear to be non-victims suffering from such 

consequences. Thus, any true impact will be biased toward zero. 

Sample Constraints

 Although the NCVS is a nationally representative sample of U.S. addresses, there 

are certain populations that are excluded from the survey. These include the homeless 

and institutionalized populations including incarcerated individuals and those living on 

military bases. Evidence suggests that incarcerated women have more violent histories 

with their intimate partners compared to women in general For example, Dugan and 

Castro (2004) found that women incarcerated in Baltimore, MD (urban, mostly Black) 

had a substantially higher rate of violent victimization (47.08% for six months) than did 

women in the NCVS (1.40% for six months). Also, they found that the risk and protective 

factors are quite different for these two groups. For example, for women in general, 

intimate partner assaults are more common by husbands within the general population, 

yet incarcerated women are more often assaulted by a non-marital partner. Additionally, 

Richie (1996) studied a group of women incarcerated at Riker’s Island and found that 

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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. 

-43-
battered women often resorted to violence either directly or indirectly as a result of their 

assault. African American battered women’s criminal activities “were seen by them as 

responses to violence or the threat of violence in their intimate relationships” (1996:127). 

While Black women were often trapped in a cycle of criminal activity and in violent 

relationships, the white battered women in her sample often used criminal activity as a 

means of exiting a violent relationship. If intimate partner violence victimization is 

associated with criminal activity and increases the risk of incarceration, national surveys 

that exclude incarcerated populations will produce deflated estimates of the prevalence of 

such violence. 

Without direct empirical evidence, some prior research strongly suggests that 

women living on military bases also have a higher risk of intimate partner violence 

(Brannen and Hamlin, 2000; McCarroll, 1999; Miller and Veltkamp, 1993). According 

to McCarroll et al. (1999:81), enhanced risk factors among this population include 

“separation from family, frequent moves, unexpected deployments, and the dangers of 

military life, including the possibility of service-connected death or injury through 

accidents, and other causes of morbidity and mortality.” Hence, the unique stressors of 

military life likely increase the risk of domestic violence. In fact, Brannen and Hamlin 

(2000:169) indicate: “Several studies have suggested that military families experience 

higher levels of aggression than families in the civilian sector because the military either 

attracts aggressive men or that the culture and training promote aggression.” Similarly, 

Miller and Veltkamp (1993:767) assert that both “the family and a multigenerational 

transfer of abuse experienced prior to service” and “the exposure to violence within the 

military” are risk factors among military personnel. Shupe, et al. (1987:67) describe "a 

-44-

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heavy emphasis on the masculinity and aggressiveness that research on civilians has 

found to be an important component of male violence toward women ." They link the 

military culture, generating and reinforcing these ideals, to prior research, but fail to 

detail specific findings. 

Other studies have directly measured the extent of intimate partner violence in the 

military. While the rates are not always directly comparable with those of other studies, 

tend to produce higher rates than those found for their civilian samples (Heyman and 

Neidig 1999; Murdoch and Nichol 1995; see also: Cronin 1995).18 Heyman and Neidig 

(1999) critique studies (i.e. Bohannon, Dosser, and Lindley 1995; Cronin 1995; Griffin 

and Morgan 1988) comparing military and civilian rates of spousal violence claiming that 

these studies are not always representative of the civilian and Army families, and do not 

typically control for demographic differences between the two populations. Their study is 

an attempt to remedy this. Heyman and Neidig focus exclusively on abuse perpetrated by 

husbands against their wives. In the early 1990s, the Conflict Tactics Scale was 

administered to a random sample of military personnel at 47 Army posts. Heyman and 

Neidig compared prevalence rates in the sample of Army respondents to comparable 

civilians in the 1985 Family Violence Survey.19 Controlling for age and race (factors 

demonstrated to affect the likelihood of abuse), they found insignificant differences in 

men’s reports of moderate husband-to-wife assault, but significantly higher rates of 

severe husband-to-wife assault in the Army sample. Women in the Army sample reported 

18 Studies of the military are often limited to the current partner or only to spousal assault and not other 

contexts of intimate partner violence. 

19 Their sample varied across demographic variables from 30,426 to 31,157. The civilian sample they 

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-45-
higher rates of both moderate and severe assault victimization. When comparing the 

Army sample to the general sample, the Army has consistently higher rates. The authors 

suggest this may be due to selectivity into the Army: those with risk factors for spousal 

abuse may be more likely to volunteer for service. 

determined was comparable (they excluded unmarried and unemployed persons) was 3,044 respondents. 

While the evidence is not definitive, there are convincing reasons to believe that 

those incarcerated or living on military bases have more experiences with intimate 

partner violence than the general population. Thus the NCVS omits at least two very 

important populations with above average victimization rates. Therefore, we can only 

generalize our findings to non-institutionalized U.S. population over age 12 who live in 

addressed residences. 

Patriarchal Terrorism or Common Couple Violence? 

 Johnson (1995) distinguishes two types of intimate partner violence: patriarchal 

terrorism and common couple violence. He notes that many feminists have identified a 

type of violence perpetrated by men to control women. This violence is frequent and 

escalates in severity and is almost exclusively perpetrated by men on women who 

typically do not fight back. He terms this type of violence against women “patriarchal 

terrorism.” Johnson also explains that this terminology only describes a small subset of 

partner violence. Those working from the family violence perspective detail a 

dramatically different picture of intimate partner violence. Their work illustrates that in 

many relationships, the violence is as equally likely to be perpetrated by the female as the 

male. Unlike patriarchal terrorism, “common couple violence” does not tend to escalate 

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-46-
over time. Johnson contends that national surveys are more likely to uncover the more 

frequent common couple violence while shelter and agency based studies are more likely 

to reveal the more rare patriarchal terrorism. The NCVS is designed to record all 

incidents of attack, regardless of how inconsequential it may seem to the respondent. In 

fact, the survey explicitly probes the respondent to recollect incidents committed by 

someone they know such as a relative or family member and asks for reports of all 

incidents even if the respondent does not consider it a crime. (Bureau of Justice Statistics 

2002). Thus, the data used here is likely to include “common couple violence” that is 

unlikely to lead to changes in marital status, residence, or employment. Therefore, biases 

due to this issue, will be towards zero. 

Underreporting 

 A large problem with any survey data is the respondents’ failure to disclose 

specific incidents. This may be exacerbated here because terrorized women may be 

likely to hide the assaults out of shame or fear. This is an issue in all studies that attempt 

to capture incident of partner violence. Schwabe and Kaslow (1984:128) explain: 

Even if we had a reliable objective definition and a consensus on how to measure 

violence, we still would face the problem of getting family members to report the 

incidents. No one likes to talk about unpleasant or embarrassing private events. 

There is also the fear that the identified abuser will retaliate with further assaults. 

Further, some victims may hide their experiences out of fear of being blamed. Dworkin 

(1993:238) describes the experiences of some women: “If you try to say you have been 

hurt and by whom and you point to visible injuries and are treated as if you made it up or 

as if it doesn’t matter or as if it is your fault or as if you are worthless, you become afraid 

to say anything.” 

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-47-
 

 While all surveys suffer from disclosure bias, other data sets produce much higher 

rates of intimate partner violence than those reported in the NCVS (see Table 1). These 

differences are likely due to the following reasons. First, the NCVS is a general crime 

survey that is collected in a formal, rapid manner by government officials. Thus specific 

probes encouraging respondents to disclose acts perpetrated by an intimate are likely to 

be lost in the barrage of questions. The context of discussion about crime more broadly 

may not trigger responses about acts that are seen as very personal in nature and may not 

be viewed as crimes (see, for example: Tjaden and Thoennes 2000a). Second, while 

many studies of intimate partner violence ask about the history of violence over the life 

course, the NCVS refers only to a maximum of three and a half years. Thus, we would 

expect rates to be lower. Finally, the denominator or the intimate partner violence rate 

includes all women regardless of whether they are intimately involved with a potential 

perpetrator—thus deflating the true rate. It is not possible to determine the number of 

women who were truly at risk (since the NCVS only has detailed information on 

marriage, but not dating relationships). However, the sample ranges in age from 12-90.20 

While, the current study retains all women for analyses, it is likely that those in the 

younger and older years are not partnered. 

 Since the data will include women who were truly victimized but appear as nonvictims, this type of measurement error will result in estimate biased toward zero. 

20 Respondents over age 90 are coded as 90. 

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-48-
Mobility

 Since the NCVS samples addresses and not individuals or households over time, 

we are concerned that non-random residential mobility will affect the findings. For 

instance, violence may occur and be followed by a victim may move immediately after 

the incident and prior to the next interview. This would appear as if a non-victim moved, 

biasing our estimates towards zero. Further, when victims of intimate partner violence 

move out and leave our sample, we are unable to record their marital or labor force 

outcomes. If these women have the most extreme labor force outcomes or are most likely 

to divorce, any findings will be biased toward zero. Finally, mobility limits our ability to 

track subsequent assaults, censoring our data prematurely. 

While each of these constraints place limits upon the generalizability of our 

results and tends to bias our estimates towards zero, this project is important and worth 

pursuing. Very little is known about the consequences of intimate partner violence and 

this is the first opportunity to examine a nationally representative data set that follows 

victims over time. This work has the potential to yield indicative findings and is valuable 

in identifying important areas for further investigation. Additionally, we carefully 

interpret findings and information, in tandem with what has already been shown in the 

literature, to inform policy and research debates about how violence affects women’s 

lives. 

Small Proportion of Victims

 Of the 50,115 women, 0.91 percent or 458 report at least one assault by an 

intimate partner. The small proportion of victims raises at least one concern. Any 

measurement error will have a magnified effect upon findings. That is, if a woman 

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-49-
misreports being violently victimized by an intimate when she was not, our estimates 

would be inflated (see: Cook and Ludwig 1998). However, after a respondent reports 

being victimized, she is asked a series of detailed questions that would be difficult to 

answer consistently had the incident not occurred. Staff is then able to adjust for 

erroneous reports. A more likely scenario is that the respondent underreports actual 

events, which would bias the analyses toward zero. We expect that this bias will offset 

any inflation due to misreported claims, thus the magnitudes of significant findings will 

be conservative. 

 RESULTS 

Household Disruption

 We estimated four sets of competing risks models to analyze household 

disruption. Table 3 presents the relative risk ratios from two stacked multinomial 

regression models run on women married at the time of the interview. The first is from 

the sample all married women, while the second is restricted to married violent crime 

victims. The first model is broken down into three contrasts: becoming divorced or 

separated relative to remaining married and living in the same home, moving out of the 

household as opposed to staying, and the entire household moving versus staying in the 

home. The second model was initially run using those three contrasts, but we found that 

very few of the victims moved without the rest of the household. To reduce the 

instability if the model, we grouped the individual movers with those who divorced or 

separated. This is discussed below. 

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-50-
 

[Table 3 About Here] 

 We turn first to the findings for the demographic variables for the full sample of 

women to demonstrate that the model is producing reasonable findings. Older married 

respondents are less likely to end their marriage or move away from their home (alone or 

with their household). Those with low income are more likely than others to have a 

change in household (either through a break-up or move). Employed, married women are 

more likely to end their marriage but less likely to move without the household. Since 

these women are more financially able to support themselves independent of their 

husband’s income, it makes sense that they are more likely than others to divorce. 

Another sensible finding is that those who own their homes, rather than rent, are less 

likely to move the entire household, while those in multiple unit dwellings are 

significantly more likely to move with their households. 

 We now turn to our primary independent variables, victimization history. To 

facilitate comparisons, we present the odds ratios for these variables in Figure 5. The 

axis is set at one, so that upward bars denote that the variable increases the odds of 

marital dissolution or moving, and downward bars signify a decrease. The graph presents 

the results for both the entire sample, and for the sample of spousal violence victims. 

First, we find that those married women with a history of intimate partner assault(s) have 

a significantly higher risk of marital dissolution than other married women, while those 

who have recently been assaulted by an intimate are more likely than other married 

women to move the entire household (not necessarily together).21 This suggests that 

21 Unfortunately, small cell sizes precluded us from estimating how intimate partner violence influences 

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-51-
 

married victims of intimate partner violence do attempt to reduce their exposure to 

violent husbands. Having said that, we must caveat that household moves could 

represent mobility with the violent spouse, instead of a break-down of the family. 

individual moves. 

[Figure 5 About Here] 

 Victims of non-violent crime also appear to have a higher risk of ending their 

marriage or moving their household than do other victimized and non-victimized married 

women. It is surprising, however, that non-intimate victimization is only weakly 

associated with mobility, given previous research suggesting property crime victimization 

does influence household moving decisions (Dugan 1999). 

 The second set of findings is drawn from the sample of married women who 

reported being a victim of at least one crime. As mentioned above, we initially produced 

the same contrasts for this sample, but found that relatively few married women moved 

from the address unless the entire household also moved. Instead of reporting unstable 

results, we combined the lone movers with those women whose marriage ended. We 

chose this strategy because it seems more likely that victims who move without their 

households (i.e., their husbands) make better proxies for troubled marriages than eventual 

household moves. 

In this model, we no longer find an influence of intimate partner violence on 

marital dissolution, suggesting that victimized women (regardless of type of 

victimization) have similar divorce patterns. However, we do still find that women who 

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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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-52-
 

were recently victimized by their husbands are significantly more likely than other 

victims to have the entire household move, suggesting possible divorce.22 

 Turning to the demographic variables for the sample of victims, we see that they 

appear to be less important compared to those from the general sample. While age is still 

negatively related to ending a marriage, it is no longer significantly associated with 

moving. Married low-income respondents no longer have an elevated risk of marital 

dissolution or moving.23 Finally, we find no evidence that any of the incident-specific 

characteristics play a role in whether the victim remains married or at the same residence. 

 Table 4 presents odds ratios from the stacked logistic models predicting whether 

the unmarried respondents moved by the following interview for both the full sample of 

respondents and the subset of violent crime victims only. As mentioned above, we 

combined individual moves with household moves since many unmarried women live 

alone blurring the distinction between the two. 

[Table 4 About Here] 

 We first examine the results for the demographic characteristics for the full 

sample and find that many have the anticipated effects. For example, similar to what we 

find for the married respondents, age and home ownership are associated with lower odds 

of moving. With the exception of Native Americans, who are more likely to move, we 

find that unmarried minority women are less likely to move than their white counterparts. 

Additionally, unmarried women who are employed have a higher risk of moving. This is 

22 There is also weak evidence to suggest that compared to other victims, nonviolent crime victims are more 

likely to end their marriage, but less likely to move the entire household 

23 However, weak evidence suggests that married victims in high-income families are now more likely to 

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-53-
 

also the case for those who attend school, those who live in a multiple unit dwelling 

and/or earn a low income—all groups who may be considered less stable (i.e., more 

mobile). The findings also show that the longer the responded lived at that address, the 

smaller the chance is that she will move. Also, unmarried public housing residents are 

less likely to move. Those unmarried women who live alone are more likely to stay 

where they are, whereas those who live with other adults are more likely to move. 

Finally, compared to white women, Native American women are more likely to move, 

whereas black, Hispanic, and Asian women have lower odds of residential mobility. 

divorce/separate. 

 Having established that the findings for the demographic characteristics make 

sense, we have more faith that the model accurately predicts the impact of victimization 

on moving for unmarried women. We find evidence that unmarried victims of violent 

crime are more likely than those not violently victimized to move within six months of 

the incident report. Specifically, those recently victimized by an intimate partner have 

1.24 times the odds of moving per incident relative to those not recently victimized by an 

intimate. This suggests that unmarried victims of partner violence use mobility as a 

method to reduce their exposure to violence. Additionally, we find that recent violent 

victimization by a stranger increases the risk of moving. Having a history of violence by 

a non-intimate (either known or unknown) also increases the chance that a single woman 

will move. Finally, when a single woman is victimized by a property crime her chances 

of moving, sooner or later, increase. These findings are more aligned with Dugan’s 

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-54-
(1999) results that found a pattern of moving after crime victimization than were our 

findings for married women. 

 Turning to our second model, restricted to victims of violent crime, we continue 

to find that those unmarried women recently victimized by an intimate are significantly 

more likely than other violent crime victims to move. Those victims whose perpetrators 

were strangers also tend to move, but usually after more than a six month period.24 

Additionally, those victims of violent crime who contacted the police may be more likely 

to remain in their current home. 

Turning to the demographic characteristics, we see that many of the associations 

for victims are similar to those of the general population of unmarried women. Age, 

black, Native American, attending school, home ownership, public housing, and living 

alone act as they did in the first model. However, we now find that Hispanic victims are 

more likely to move than whites. Finally, victims living in the city and those unmarried 

victims who were previously married move less. 

Entering/Exiting the Labor Force

 Figure 4 illustrates the bivariate findings by following the employment patterns of 

all intimate partner violence victims on a probability tree. Of the 458 victims in the 

sample, we know the employment status of 445 at both the first incident and the 

following interview. Of these women, 305 were employed at the first incident, the 

remaining 140 were not. Just over ten percent of those employed left the labor force by 

24 This model also weakly suggests that women who were injured are more likely to move. 

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-55-
the following interview. Of those not employed at the time of the first incident, 20% 

entered the labor force. 

[Figure 4 About Here] 

 Table 5 presents the odds ratios for the discrete hazard models predicting entry 

into the labor force. The first model is run on all interviews where women previously 

reported that they were not employed (at prior interview, or at first reported crime 

incident for victims). The second model repeats the first on victims of violent crime. In 

addition to all of the variables from the first model, it includes the intervening measures 

and incident specific controls. We begin our discussion by focusing on the first model 

for all females in the sample. 

[Table 5 About Here] 

 It is worth noting up front is that the control variables act as expected. Older 

women are less likely to enter the labor force (since the odds ratio of Age is less than 

one). This estimate is likely capturing the patterns of retired older women who are 

unlikely to re-enter the labor market. The findings also show that non-working Hispanic 

and Asian women are less likely than non-working white women to enter the labor force. 

Also not surprising, unemployed women with less education are less likely to enter the 

labor force, while those with at least some college are more likely. Many employers use 

education as a hiring standard. Similarly, low income, unemployed women are less likely 

to enter the labor force than those of moderate means. Also, non-working married 

women are less likely than their single counterparts to start working. In contrast, nonworking divorced women are more likely to become employed. Since married women 

can often rely on their spouse’s income for support, employment is less crucial than to the 

-56-

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single women. Whereas divorced and separated women may find it necessary to work to 

replace income lost when the marriage dissolved. 

 Another expected finding is that those not working and attending school are less 

likely to transition into the labor force. They generally have less time available to work. 

Also, those non-working women who reside at their address longer are less likely to enter 

the labor force. Longer time at residence is likely indicative of stability, thus, all other 

factors equal, those living in their homes longer may have less need to seek employment. 

Residing in a multi-unit dwelling slightly increases the odds of a labor force entry. 

Perhaps these respondents are mostly renters who have a higher need to regain 

employment. Another indicator of transient, less stable housing may be reflected in 

households with multiple adults. Non-working women in these homes have higher odds 

of entering the labor force. In contrast, when these women live with more children they 

are less likely to enter the labor force. Having children makes it costly to work, given the 

expense of childcare. Another very strong finding (that is expected) is that if the nonworking respondent previously reported that she did work, she is more likely to regain 

employment before exiting the survey period. Since these women only recently became 

unemployed, they are more likely to be heavily engaged in a job search. 

 The above findings demonstrate that the model is behaving as expected. With this 

in mind, we now turn to our key predictors: victimization. This model provides no 

evidence that being victimized by an intimate partner significantly influences the 

likelihood that a woman will enter the labor force. This non-finding is especially 

intriguing because the other results also show that when a non-working female is 

violently victimized by another offender (or is the victim of nonviolent crime) she is 

-57-

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highly unlikely to enter the labor force. Thus, whatever prevents unemployed victims 

from entering the labor force within six months of the incident appears to have no impact 

if the perpetrator was an intimate. 

 The findings in the second model that conditions on women who were violently 

victimized at least once have similar patters with a few notable exceptions. When these 

women are victimized by someone other than their partner, their chances of immediately 

entering the labor force remains the same instead of decreases.25 

 The findings for race differ in the sample of violent crime victims compared to the 

total sample of women. This is not surprising since the racial distribution of victims 

differs dramatically from the distribution of all women (Dugan and Apel 2003). Also, 

note that the dramatic drop in the sample makes it impossible to retain high counts in all 

racial and ethnic categories. Not enough Asian women were victimized to allow the 

models to estimate an “Asian” effect. Thus, we would not expect to see the same 

findings for race. Having said that, black, non-working victims of violent crime are only 

half as likely as white victims to enter the labor force. Hispanic and Native American 

women are dramatically more likely to begin work. Many of the conditions that seem to 

predict whether a non-working woman entered the labor force failed to do so for victims 

of violent crime. A victim’s educational attainment surprisingly has no influence on her 

odds of entering the labor force. Also divorced victims are no more likely to enter the 

labor force than are single victims. Finally, attending school, living in multi-unit 

25 There is weak evidence that a non-working victim of intimate partner violence is likely to enter the labor 

force within six months of being assaulted by her partner (OR = 1.42, p< 0.10). Weak evidence also 

suggests that a victim with a history of stranger violence is likely to enter the labor force. 

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-58-
dwellings (or public housing), and living with a large number of adults, have no effect on 

victim’s chances of a entering the labor force. These null findings could suggest that the 

condition of having been violently victimized is more important than the typical 

background characteristics in predicting a transition into the labor force. 

 Turning to the intervening variables, we find that having been injured enough to 

seek medical attention (and therefore seeking that attention) is associated with three times 

the likelihood of entering the labor force. This is the only action at the time of the 

victimization that seems to predict labor force entry. Self-defense, injury, and a victim’s 

notification to the police have no significant impact. Perhaps a victim needs employment 

to finance the costs of seeking medical assistance. Or, perhaps victims of intimate 

partner violence who seek medical help experience a “wake-up call” making apparent the 

precariousness of their situation. Seeking employment may be the first step to gaining 

independence from the abuser. Finally, if the medical profession is screening for victims 

of domestic violence, perhaps by interacting with the medical profession, a victim may 

have more opportunities opened to her. The other significant finding reveals that nonworking victims of series violence are dramatically less likely to enter the labor force. 

Such repeat violence likely interferes with life, making it difficult to add any additional 

responsibility. 

 In Table 6, we display the odds ratios generated from the models for exiting the 

labor force. Like Table 5, it contains two models: one using the sample of all women 

employed at the time of interview (first incident for victims) and one using the subsample of violent crime victims. 

[Table 6 About Here] 

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

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

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

 As expected, the findings generated from the sample of all women produce 

control variable estimates that make sense. These findings are consistent with those for 

labor force entries shown in Table 5. Older employed respondents are more likely to exit 

the labor force (i.e., retire). Employed women with less education more often stop 

working while those with more than a high school degree more often remain employed. 

Low income employed women leave the labor force at higher rates than their peers in 

middle-income homes. Divorced employed women are more likely than single women to 

remain in the labor force. Employed students are more likely to stop working. Those 

workers who have lived in their home longer are more likely to exit the labor force. 

Employed women living in public housing are more likely to leave their job. Living 

alone decreases the likelihood that a working woman will leave the labor force. Yet, 

living with more than one other adult increases the likelihood that she exits the labor 

force. Each child in the home decreases the odds that an employed woman leaves her 

job. Having been unemployed in an earlier interview increases the likelihood that a 

woman will again be unemployed before leaving the sample. 

 However, there are some findings that could not be anticipated from the early 

labor force entry findings. The racial and ethnic characteristics are barely significant and 

differ from those in Table 5.26 Working Native American women are more likely than 

whites to leave their job. 

 These analyses strongly suggest that a working woman’s history of violent 

victimization has no effect upon her odds of exiting the labor force. However, they do 

26 Weak evidence suggests that employed black women are less likely than employed white women to exit 

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. 

-60-
suggest that if she suffers from a property crime she will is less likely than other 

(victimized and nonvictimized) women to leave the labor force within the next six 

months. We find, though, that her chances of leaving increase over time. 

the labor force. 

 The victimization estimates remain null when we limit the sample to only those 

employed women who have suffered from violence, indicating that victims of intimate 

partner violence do not differ from other violent crime victims. Additionally, the effect 

of age reverses for these women. Older working victims of violence are less likely to exit 

the labor force than younger victims. Further, while race and education were more 

important in the victim models for entering the labor force, they appear to be irrelevant to 

a working victim’s decision to exit the labor force. Also, attending school, length of 

residence at the current address, living in public housing, living with more than one other 

adult and interview period are not significant predictors of victim’s labor force exits. 

 Finally, it appears that any action taken by the working victim at the time of the 

incident is unrelated to her decision to leave the labor force. We find no influence of 

self-defense, injury or help seeking on the odds of a labor force exit. The only incident 

characteristic that seems relevant is a history of weapon use against the victim. Those 

women ever victimized with a weapon are 1.74 times more likely to exit the labor force 

than are other violent crime victims. 

Repeat Assault

Our final model estimates how different intermediate behaviors and 

characteristics affect the likelihood that an intimate partner victim is re-victimized. Table 

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. 

 

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7 displays the distribution on the four primary intermediate variables: self-defense, 

injury, medical care, and police contact. Nearly a quarter of all victims reported at least 

one repeated assault. When we compare the distribution of characteristics for victims 

who only suffered from one assault with those who were re-victimized, we find little 

difference. The only distinguishing feature is that those with only one assault were more 

likely to have personally contacted the police (50% versus 39%). This suggests that 

police notification may be associated with a lower likelihood of subsequent assault. 

Perhaps this relationship is direct where the police intervention stopped further assaults. 

However, this could also be a selection effect whereby those who respond against the 

violence (i.e., call the police) are also more likely to get themselves out of harm’s way. 

[Table 7 About Here] 

The general distributions of the remaining characteristics are as follows. 

Relatively few victims, 11% and 14%, acted in self-defense during the first assault. 

Nearly half of the victims reported an injury following the first reported assault. 

Similarly, nearly half of those injured sought medical help. Also worth noting is that 

those who reported a subsequent intimate partner assault were significantly less likely to 

have left the labor force after their first assault [Data Not Shown]. This suggests that by 

leaving the labor force, the victims may effectively escape the violence. Perhaps by 

leaving the labor force a woman is forced into a more traditional role, no longer 

threatening her partner’s sense of security reducing his need to resort to violence to 

control her. Alternatively, it could signify a short-term strategy to change her life so that 

she can better escape a violent relationship. 

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
The NCVS also includes questions about whether the victim was previously 

victimized by the same offender. While this only discloses information about acts 

committed by the same person, the information can be used to indicate known 

victimizations before the respondent entered the survey period. By tabulating this 

variable we see that 42% of those we considered “one time” victims had actually been 

assaulted by the same partner before. This reinforces our concern that our findings are 

likely biased toward zero. We also find that 41% of those with subsequent victimizations 

were assaulted by the same assailant prior to the survey reference period. We control for 

an offense by the same offender in the below multivariate models. 

Additionally, the findings in Table 7 compare victims regardless of when they 

first reported an assault. Since those who report their first assault in a later interview 

have relatively less time to be re-victimized compared to those who report one earlier, 

one might expect higher rates of subsequent assault for those reporting a first assault 

earlier. Thus, our multivariate models also control for the interview period. 

In Table 8, we present the odds ratios from the multivariate stacked logistic model 

predicting a subsequent intimate partner assault within six months prior to interview. It 

includes all of the controls, incident characteristics, our labor force changes and marital 

dissolutions and is restricted to those interviews reporting at least one prior or current 

incident of intimate partner violence. This model surprisingly shows that a larger number 

of previous intimate partner assaults is associated with a lower, not higher, likelihood of 

reporting a subsequent assault. Specifically, each prior intimate partner assault is 

associated with having about a quarter the odds of repeat assault. However, women who 

were previously violent victimization by another known person or were recently a victim 

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
of property crime are at substantially higher risk of a repeat assault by an intimate. None 

of our intervening variables have significant effects upon the chances of repeat assault, 

with the exception of self-defense. Those who defend themselves from their perpetrator 

have an increased likelihood of subsequent assault. Although this is only marginally 

significant, it could indicate a retaliatory effect. Our other, non-findings for the 

intervening variables suggest that sustaining an injury and a victim’s actions at the time 

of or immediately following assault have virtually no influence on whether or not she is 

assaulted again by an intimate. Thus, when the victim has contact with the medical 

system or calls to the police, she does not seem to be either increasing or decreasing her 

safety. 

Turning to our employment and marital consequences of intimate partner 

violence, we find that by leaving the labor force, a victim decreases her odds of being reassaulted. However, we also find that by entering the labor force a victim does not 

significantly alter her risk of being assaulted again by an intimate. As mentioned above, 

exiting the labor force could either represent attempts to appease the abuser or signify the 

beginning stages of a strategy to exit the violent relationship. Another important null 

finding is that those victims who recently ended their marriage appeared to be no more 

(and no less) likely than other women to be re-assaulted. 

Other interesting findings are that blacks are far less likely than whites to sustain a 

subsequent assault, while Hispanics are at far greater risk. Those victims living in public 

housing are more likely to be re-assaulted. Having more adults in the home increases 

risk, while children seem to protect victims from re-assault. Perhaps the presence of 

children makes women more safety-conscious so that the children are not exposed to 

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

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

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

violence. Also, as expected, those whose first assault was later in the survey period 

reported fewer repeat assaults, and those reporting during a bounding interview were 

more likely to report repeated assaults. 

Finally, the findings for the incident control variables indicate that the victim is 

less likely to be subsequently assaulted if the offender used a weapon during an earlier 

assault. Perhaps the threat of a weapon motivated the victim to better protect herself 

from dangerous intimate. We also find in this set of results that the chances of re-assault 

are also reduced if the police were previously contacted by a third party following an 

earlier intimate partner assault. Re-assault is also less likely if the victim’s perpetrator 

was arrested after an earlier assault. These latter two findings suggest that contact with 

the police can protect the victim. Yet, this raises an important question as to why the 

police seemed to have no effect when the victim calls the police herself. It suggests that 

calls by others are taken more seriously by the police. 

If the perpetrator was under the influence of drugs or alcohol during an earlier 

incident, the woman is more than twice as likely to report at least one subsequent assault. 

This is consistent with literature that links alcohol and drug dependency with the 

perpetration of intimate partner violence (see: Crowell and Burgess 1996). Those who 

previously experienced intimate partner violence as a series of incidents had 174 times 

the odds of being assaulted again compared to those without a series assault.27 This is the 

least surprising finding since by definition, a series assault represents at least six 

incidents—thus the victim is by definition, a repeat victim. Having said that, the findings 

27 This strong finding is not unexpected, as by definition, series assaults represent six or more similar 

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. 

-65-
also show that those who reported that the perpetrator had done something similar in the 

past are at lower risk of repeat assault. This is an unexpected finding since those women 

are also, by definition, repeat victims (although they are not coded as such). 

incidents. There is already evidence of ongoing violence and this finding suggests that it persists. 

Results

 This project contributes substantially to our understanding of how intimate partner 

violence impacts women’s lives. We begin by describing the basic characteristics of the 

women and the changes they go through after being attacked by their partners. Because 

to date, most of what we know about these women’s experiences relies on cross-sectional 

or localized, non-representative studies, our project takes the first step toward 

understanding the patterns of changes women generally experience after violence. 

 We guided this research by asking whether victims are inclined to reduce their 

exposure to the intimate perpetrator after an incident. We then consider whether those 

choices actually do lead to reduced violence (hypothetically, because they worked), or if 

they entice more violence (hypothetically, because the perpetrator retaliated against her 

actions). We approached these general concepts by asking three, more specific, 

questions: 

1. Are intimate partner violence victims more likely than other women to 

divorce or move out of their home within six months of a reported assault? 

2. Are intimate partner violence victims more or less likely than other women to 

leave or enter the labor force within six months of a reported assault? 

3. What factors are associated with reports of repeat assault? 

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. 

 

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We also considered how a victim’s injuries and actions at the time of (or immediately 

following) assault influenced all three outcomes. 

 The answer to our first research question is a resounding “yes.” Married victims 

of intimate partner violence are more likely than other women to divorce or move. We 

also found that unmarried victims of partner violence, including those who live with an 

intimate28, are indeed more likely to move fairly quickly after their boyfriends attack 

them. This appears to be a common coping strategy for the unmarried woman, because 

she is also more inclined to move if she is violently victimized by a stranger or even if 

she is a victim of property crime. We also find that very few actions that a married 

victim takes during or immediately after the incident influences her choice to move. 

However, if an unmarried woman calls the police, she appears less likely to move. 

Perhaps she feels that the police will provide enough protection making her move 

unnecessary. However, we found that if she was injured during the event, she is more 

likely to move. This could be a wake-up call to the dangers of remaining in her home. In 

sum, it does, indeed, appear as if the victim of partner violence will leave the relationship 

through divorce or moving to reduce her exposure to the perpetrator. 

 Our findings fail to provide such a clear-cut answer to the second research 

question. We find no evidence that working women are any more or less likely to leave 

their jobs after violence. We do, however, find evidence that unemployed victims of 

crime are less inclined to find a job within six months of the incident. However, the 

exception to this rule is for those victims who have an intimate relationship with their 

28 The NCVS does not allow us to determine if respondents cohabit with an intimate partner. 

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. 

-67-
perpetrator. In fact, their patterns look more like those for non-victims. This changes 

when we restrict the analysis to only victims of violent crime. Given that the 

unemployed woman is a victim of violent crime, if her perpetrator was her boyfriend or 

husband, she is marginally more likely to find a job fairly soon after the incident. 

Perhaps she is finding work as part of a strategy for becoming more independent of (and 

less exposed to) her violent partner. We also found that when the unemployed victim 

was injured to the extent that she sought medical care, she was more likely to find a job. 

Both seeking medical help and entering the labor force could represent a victim’s agency 

toward reducing her exposure to violence. 

 Finally, our third research question was designed to determine whether exposure 

reduction leads to less or more violence. The results are mixed. It appears that if a 

victim acts in self-defense, she may be setting herself up for later attacks. While we 

cannot be certain that the latter attacks are from the same perpetrator, if they are, this 

would be strong evidence that he is retaliating against her self-defensive actions. We 

unexpectedly found evidence that some victims who increase their exposure to their 

partner could actually be decreasing their chances of further perpetration. It seems that 

those working women who leave the labor force after an attack are protected from further 

attacks. We clearly cannot draw strong conclusions about this method of protection 

without knowing the specific contexts of those women who leave their jobs. We have no 

idea whether the victim is, indeed, spending more time with her perpetrator, or whether 

she is preparing to make a larger break from home. While we find no direct evidence that 

a victim’s own exposure-reducing behavior affects on her chances of re-victimization, 

when others act to reduce her exposure, such as others’ calls to police and arrests, her 

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
chances of re-victimization drops. This suggests that policies implemented to reduce a 

victim’s exposure to the perpetrator may improve her safety. 

 In sum, our analyses offer more straightforward support for retaliation effects than 

for exposure reduction (unless, of course, others reduce the exposure for the victim of 

intimate partner violence). However, there are limitations of this project that need to be 

acknowledged. Since this is a victimization study, we have no information on the 

perpetrator’s motives. Further, we cannot be sure that subsequent assault was perpetrated 

by the original offender. While we suspect this is true, further studies are necessary to 

disaggregate motives and test whether or not subsequent assaults are indicative of 

retaliatory violence. 

 We also find that violent crime victimization and intimate partner violence, in 

particular, are important predictors of changes in household composition and 

employment status. While we speculate that these changes were done to reduce the 

victim’s exposure to violence, further research is needed to more specifically examine the 

reasons behind these changes. Our research represents an important contribution to 

extant findings. Future research can improve on our work by integrating the explicit 

nature and entire history of intimate partner victimization for each woman. Studies 

should also continue to follow a nationally representative sample of women, even if they 

move. This way, we will learn more about the longer-term consequences of violence. 

 While these findings fall short of providing cut and dry policy recommendations, 

they do suggest important roles for the police and medical establishments. If, indeed, 

victims’ lives improve when outsiders help them, then the medical and criminal justice 

systems should continue to direct their efforts toward assisting victims. Additionally, 

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

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

and do not necessarily reflect the official position or policies of the U.S. Department of Justice. 
education programs could let the public know that they are protecting the victim by 

calling the police during a domestic dispute. Null findings from many of our models 

suggest that these institutions can do more to aid battered women. Additionally, the 

finding that self-defensive actions increase a woman’s risk of subsequent intimate partner 

assault suggests that we need to pay more attention to all victims of partner violence. 

Women who choose not to use shelters may be more likely to attempt to deal with the 

violence on their own. These same women may also avoid calling the police, heightening 

the chances that they will rely exclusively on self-defensive behaviors. This strongly 

implies that any efforts to protect women who are actively resisting the violence in their 

lives may be beneficial. 

 

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

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

1 Completed Rape

2 Attempted Rape

3 Sexual Attack with Serious Assault

4 Sexual Attack with Minor Assault

5 Completed Robbery with Injury from Serious Assault 

6 Completed Robbery with Injury from Minor Assault

7 Completed Robbery without Injury

8 Attempted Robbery with Injury from Serious Assault

9 Attempted Robbery with Injury from Minor Assault

10 Attempted Robbery without Injury

11 Completed Aggravated Assault with Injury

12 Attempted Aggravated Assault with Weapon

13 Threatened Assault with Weapon

14 Simple Assault Completed with Injury

15 Sexual Assault without Injury 

16 Unwanted Sexual Contact without Force

17 Assault without Weapon without Injury

18 Verbal Threat of Rape

19 Verbal Threat of Sexual Assault

20 Verbal Threat of Assault

Other Crimes

Personal Theft

21 Completed Purse Snatching

22 Attempted Purse Snatching

23 Pocket Picking (completed only)

24 Completed Personal Larceny without Contact Less than $10

25 Completed Personal Larceny without Contact $10 to $49

26 Completed Personal Larceny without Contact $50 to $249

27 Completed Personal Larceny without Contact $250 or greater

28 Completed Personal Larceny without Contact Value NA

29 Attempted Personal Larceny without Contact

 Household Crimes

31 Completed Burglary, Forcible Entry

32 Completed Burglary, Unlawful Entry without Force

33 Attempted Forcible Entry

34 Completed Household Larceny Less than $10

35 Completed Household Larceny $10 to $49

36 Completed Household Larceny $50 to $249

37 Completed Household Larceny $250 or Greater

38 Completed Household Larceny Value NA

39 Attempted Household Larceny

40 Completed Motor Vehicle Theft

41 Attempted Motor Vehicle Theft

Appendix A: Classification of Crimes

Source: Bureau of Justice Statistics (2000)

Intimate Partner Violence includes any violent crime incident (1-20) and 

burglaries/attempted forcible entries (31-33) perpetrated by a spouse, exspouse, boy/girlfriend or ex-boy/girlfriend.

Violent Victimization by another known offender includes any violent 

victimization (1-20) perpetrated by non-intimate relatives, friends/former 

friends, roommates/boarders, schoolmates, neighbors, or other nonrelated, 

identifiable individuals.

Violent Victimization by a stranger includes any violent victimization (1-

20) perpetrated by someone unknown to the victim.

Nonviolent Crime Victimization includes any other crimes (21-41) 

perpetrated by anyone except burglaries/attempted forcible entries (31-33) 

perpetrated by a spouse, ex-spouse, boy/girlfriend or ex-boy/girlfriend.
Survey Question(s) Operationalizatio

Outcome Variables

Exiting the Realtionship

Marital Dissolution Marital Status THIS/LAST Survey Period Married in t; 

Divorced/Separated in Yes/No

Individual Residential Mobility Reason for Noninterview Move between t and t+

Yes/No

Household Mobility Household Composition Code; Household Number Move between t and t+

Yes/No

Employment Consequences

Movement into/out of the Labor Force Did you have a job at the time of the incident?, then in subsequent waves: Did you 

have a job or work at a business last week? (Do not include volunteer work or work around the house.) Did you have a job or work at a business during the last 6 months? Did that (job/work) last 2 consecutive weeks or more?

Entry into/Exit from thforce between incidentt+1: Yes/No

Subsequent Victimization Multiple Intimate partner Assaults During a Survey Period or Reported Incident(s) 

of Intimate Partner Violence Reported in a follow up panel of the NCVS.

Subsequent Assault: Y

Appendix B: Dependent VariablesNote: Missing values for dependent variables were not imputed. 

Theoretical Constructs

Source: Bureau of Justice Statistics (2000)
Survey Question(s) Operationalization Treatment of Missing Data

Independent Variables

Victimizationsa

Reported Incident(s) of Intimate Partner Violence at t, Violence by Other Known Offender at t, Violence by a Stranger at t, and Nonviolent Crime Victimization at t.

Count for Each Type of Victimization Reported in t

Reported Incident(s) of Intimate Partner Violence prior to t, Violence by Other Known Offender prior to t, Violence by a Stranger prior to t, and Nonviolent Crime Victimization prior to t.

Average for Each Type of Victimization Reported Prior to t.

Intervening Variables If no evidence, then assigne

Self-Defensive Actions at the Time of Did respondent use or threaten to use 

physical force against the offender? Who was the first to use or threaten to use physical force - you, the offender, or someone else?

Self Defense: Yes/No

Injury following Intimate PartnerWhat were the injuries you suffered, If any? 

Anything else?

Indicator, Coded (1) if injuy sustainbed after any Intimate Partner Violence Incident reported in t, else (0).

Were you injured to the extent that you received any medical care, including self treatment? Where did you receive this care? Anywhere else?

Indicator, Coded (1) if medical attention sought for injuries resulting from intimate partner violence reported in t, else (0). Care received at the scene or at home.a friend's/ neighbor's is excluded since it does not represent seeking help via the medical establishment.

Were the police informed or did they find out about this incident in any way? How did the police find out about it?

Indicator, Coded (1) if the victim notified the police after an incident of Intimate Partner Violence reported in t, else (0).

Appendix C: Independent and Intervening Variables

Theoretical Constructs

Recent Crime VariablesPrevious Crime VariablesInjured and Sought Medical Attention for Injuries Victim Notified the Police follow
Survey Question(s) Operationalization Treatment of Missing Data

Demographic Characteristics

Age Age last Birthday (Allocated) Age in years. For all women, began at Wo

interview. Incremented by 0subsequent interview.

Race For all women, assigned rac

interviews the value reporteinterview. Category "missinremaining missing cases.

Reported Race/Hispanic Origin at First Interview

Indicator, Coded (1) if reported race is white, else (0).

Reported Race/Hispanic Origin at First Interview

Indicator, Coded (1) if reported race is black, else (0).

Reported Race/Hispanic Origin at First Interview

Indicator, Coded (1) if reported race is Asian, else (0).

Reported Race/Hispanic Origin at First Interview

Indicator, Coded (1) if reported race is Native American, else (0).

Reported Race/Hispanic Origin at First Interview

Indicator, Coded (1) if reported race is Hispanic, else (0).

Education What is the highest grade or year of regular 

school ... has ever attended?)

If missing at t and value at tthen value at t=value at t-. Omissing values t1-t5. Categocreated for remaining missin

Less than 12 Years Indicator, Coded (1) for less than 12 years 

of education, else (0).

12 Years Indicator, Coded (1) for 12 years of 

education, else (0).

More than 12 Years Indicator, Coded (1) for more than 12 years 

of education, else (0).

Household Income Household Income collected in 14 

categories.

If missing at t and value at tthen mean of t-1 value and tworks for missing values t1flag created. Category "misremaining missing cases.

Low Income Indicator, Cided (1) if less than $15,000, 

else (0).

High Income Indicator, Cided (1) if greater than $75,000, 

else (0).

Theoretical Constructs

Black, non-HispanicAsian, non-Hispanic Native American, nonHispanicWhite, non-HispanicHispanic

Appendix C: Independent and Intervening Variables (continued)
Survey Question(s) Operationalization Treatment of Missing Data

Marital Statusb Marital status THIS survey period If missing at t and value at t

then mean of t-1 value and tworks for missing values t1flag created. Category "missremaining missing cases.

Married Indicator, Coded (1) if married, else (0).

Divorced Indicator, Coded (1) if divorced/separated, 

else (0).

Single Indicator, Coded (1) if single, else (0).

Employment Statusb Did you have a job or work at a business 

last week? Did you have a job or work at a business during the last 6 months? 

Indicator, Coded (1) if employed at t, else (0).

If missing and status at t-1 wat t+1, coded that value. Onmissing values t1-t5; imputacreated. Category "missing" remaining missing cases.

Student Status Attending school Indicator, Coded (1) if student at t, else (0). If missing at t and value at t

then value at t=value at t-1. missing values t1-t5; imputacreated. Category "missing" remaining missing cases.

Tenure How long have you lived at this address? 

(months) How long have you lived at this address? (years)

Months at Address. For all women, Converted R

time period to months by mby 12 and adding months. Bfirst report, incremented by value assigned to misisng vaimputation flag created.

Home Ownership Tenure (Allocated) Indicator, Coded (1) if own home, else (0). If missing at t and value at t

then value at t=value at t-1. missing values t1-t5.

Multiple Unit Dwelling Number of Housing Units in Structure Indicator, Coded (1) if multiple unit 

dwelling, else (0).

Assigned multiple unit dwelinterviews the value reporteinterview.

Public Housing Public Housing (Yes/No) Indicator, Coded (1) if public housing, else 

(0).

Assigned public housing stainterviews the value reporteinterview.

Urbanicity Land Use Indicator, Coded (1) if urban, else (0). Assigned urbanicity at all in

value reported at first interv

Appendix C: Independent and Intervening Variables (continued)

Theoretical Constructs
Survey Question(s) Operationalization Treatment of Missing Data

Household Composition

Lone Adult Household Indicator of only one household member 12 

years of age and over 

Indicator, Coded (1) if only one adult, else 

(0).

Imputation Not Necessary.

Many Adult Household Indicator of more than two household 

members 12 years of age and over 

Indicator, Coded (1) if more than two adults, else (0).

Imputation Not Necessary.

Number of Children Number of household members under 12 

years of age (0-9)

Count Imputation Not Necessary.

Employment Stability

Proportion of Previous Interviews not EmployedProportion of Previous Interviews Employed

Interview Characteristics

Interview Period Created based upon year and quarter, panel 

and rotation group

Range is 1-6.

Interview Conducted Via Proxy Type of Interview Indicator, Coded (1) if proxy interview, else 

0.

Unbounded Interview First Interview with Woman Indicator, Coded (1) if interview is the first 

with the respondent interview, else 0.

Incident Characteristics If no evidence, then assigne

Were the police informed or did they find out about this incident in any way? How did they find out about it?

Indicator, Coded (1) if someone other than the victim contacted police, else 0.

Perpetrator Arrested As far as you know, was anyone arrested or 

were charges brought against anyone in connection with this incident?

Indicator, Coded (1) if arrest/charges, else 0.

Weapon Use Did the offender have a weapon such as a 

gun or knife, or something to use as a weapon, such as a bottle or wrench?

Indicator, Coded (1) if weapon used, else (0).

Was the offender drinking or on drugs, or don't you know?

Indicator, Coded (1) if perpetrator was under the influence, else (0).

6 or more similar incidents about which the respondent cannot recall enough individual 

detail todistinguish.

Indicator Coded (1) to indicate at least one series incident, else (0).

Was this the only time this offender 

committed a crime or made threats against you or your household? Were all, some, or none of these [series] incidents done by the same person(s)?

Indicator Coded (1) to indicate offender acted more than once, else (0).

bEmployment and Marital Status were only imputede after constructing the dependent variables.

Note: Not all variables are in all models. For example, marital dissolution models are limited to those married at t; marital status is not included in these models.

aSeries incidents are counted as six incidents, the minimum number required to be considered a series.

Police Notification by Someone Other than the VictimSeries Incidenta

Theoretical Constructs

Intimate Partner Offender Did This Before

Appendix C: Independent and Intervening Variables (continued)

Source: Bureau of Justice Statistics (2000)

Perpetrator Under Influence of Drugs/Alcohol
Mean 

/Percent 

(Standard 

Deviation)

Mean 

/Percent 

(Standard 

Deviation)

Mean 

/Percent 

(Standard 

Deviation)

Divorce 0.40% 0.59% 1.14%

Individual Residential Mobility 1.85% 3.63% 3.75%

Household Mobility 4.14% 6.71% 9.86%

Entry into the Labor Force 5.77% 6.27% 5.52%

Exit From the Labor Force 5.65% 6.53% 7.09%

Subsequent Intimate Partner Assault -- -- 11.26%

Victimizations

Recent Intimate Partner Violence 0.01 0.15 --

(0.13) (0.68)

Previous Intimate Partner Violence 0.00 0.09 0.59

(0.08) (0.44) (0.58)

Recent Violence by Other Known Offender 0.01 0.25 0.04

(0.15) (0.76) (0.24)

Previous Violence by Other Known Offender 0.01 0.18 0.03

(0.11) (0.55) (0.14)

Recent Violence by a Stranger 0.01 0.19 0.01

(0.12) (0.60) (0.12)

Previous Violence by a Stranger 0.01 0.14 0.01

(0.08) (0.39) (0.09)

Recent Nonviolent Crime Victimization 0.08 0.24 0.29

(0.35) (0.71) (0.84)

Previous Nonviolent Crime Victimization 0.06 0.19 0.24

(0.24) (0.52) (0.70)

Intervening Variables

Self-Defense -- 10.07% 12.82%

Injury -- 29.50% 45.47%

-- 6.97% 9.71%

Victim Notified the Police -- 40.41% 49.04%

Demographic Characteristics

Age 42.3 32.16 31.77

(19.48) (15.23) (10.71)

Race

White, non-Hispanic (Reference/Omitted Category) 73.61% 73.23% 71.20%

Black, non-Hispanic 12.76% 15.14% 18.54%

Hispanic 9.69% 9.22% 6.89%

Asian, non-Hispanic 3.36% 0.87% 0.88%

Native American, non-Hispanic 0.39% 1.38% 2.42%

Race Missing 0.19% 0.16% 0.07%

Education

Less than 12 Years 17.28% 20.26% 12.33%

12 Years (Reference/Omitted Category) 24.77% 20.30% 23.17%

More than 12 Years 29.02% 27.57% 27.26%

Education Missing 28.92% 31.87% 37.24%

Household Income

Low Income 18.45% 24.63% 34.46%

High Income 11.86% 9.60% 5.43%

Income Imputed 0.59% 0.72% 0.94%

Income Missing 14.46% 9.66% 10.36%

Marital Status

Married 49.68% 29.22% 16.67%

Divorced 12.15% 22.65% 47.74%

Single 37.66% 47.89% 35.42%

Marital Status Imputed 0.33% 0.18% 0.40%

Marital Status Missing 0.51% 0.24% 0.17%

Employed 51.62% 56.46% 70.44%

Employed Imputed 4.89% 8.90% 1.69%

Employed Missing 7.68% 12.87% 2.19%

Attending School 7.49% 10.31% 12.05%

Attending School Imputed 2.51% 4.77% 0.91%

Attending School Missing 4.46% 8.00% 1.24%

Tenure 123.57 83.30 61.76

(140.12) (100.15) (79.09)

Tenure Imputed 0.32% 0.21% 0.47%

Home Ownership 69.32% 56.64% 48.07%

Multiple Unit Dwelling 24.07% 29.68% 33.48%

Multiple Unit Dwelling Missing 0.07% 0.17% 0.21%

Public Housing 2.28% 4.29% 4.15%

Public Housing Missing 68.68% 54.94% 46.71%

Urbanicity 73.66% 77.61% 75.82%

Household Composition

Lone Adult 16.89% 21.03% 36.41%

Many Adults 37.99% 44.52% 34.00%

Number of Children 0.55 0.77 1.01

(0.93) (1.08) (1.13)

Proportion of Prior Interviews Employed 0.37 0.44 0.52

Proportion of Prior Interviews Not Employed 0.30 0.24 0.20

Proportion of Prior Interviews Married 0.39 0.26 0.19

Proportion of Prior Interviews Not Married 0.35 0.55 0.57

Interview Characteristics

Interview Period 3.00 3.41 3.34

(2.00) (1.97) (2.06)

Interview Conducted Via Proxy 3.61% 2.29% 1.11%

Unbounded Interview -- -- 24.21%

Incident Characteristics

-- 25.11% 15.18%

Perpetrator Arrested -- 16.62% 26.09%

Weapon Use -- 24.82% 17.83%

Perpetrator Under Influence of Drugs/Alcohol -- 28.25% 42.21%

Series Incident -- 6.05% 7.14%

IPV Offender Acted Before -- -- 40.01%

Sample Size (Woman Interviews) 166,523 5,801 1,155 a

Valid N refers to the number of woman interviews.

Appendix D: Weighted Descriptive Statistics on All Variables

Note: Intervening and Incident Variables refer to those used in models run on all violent crime victims/all intimate partner violence 

victims. For all violent crime victims, they refer to any incident prior to current interview; for intimate partner violence victims, they ref

Police Notification by Someone Other than the Victim

All Women Violent 

Crime 

Victims

Intimate 

Partner 

Violence 

Victims

Dependent Variables

Independent Variables

Exiting the Relationship

Employment Consequences

Injured and Sought Medical Attention for Injuries 
Figure 1: Analytical Model

(A)

Current and 

Past Intimate 

Partner 

Violence

(B)

Exiting the Relationship

Employment Consequence

(D)

Subsequent Intimate Partn

Violence

(C)

Self-Defense

Injury

Police Notification

Medical Intervention
t Incident t+1

X = measure employment *=Collection of Race, Class, Demographic 

Interview Characteristics

+Note that 60% of intimate partner violencinformation at t because they report an assinterview.

X X*

X X* +

Figure 2: Coding of Employment Status C

Victim 

between t 

and t+1

Non-victim 

between t 

and t+1
Figure 3: Coding of Recent and Previous A

Example: Coding of Intimate Partner Victimization for a Hyp

t0 t1 t2 t3 

20. 1

t0 t1 t2 t3 20010 2 1 1 

Number of 

IPV Incidents 

Reported

Coding of 

Recent and 

Previous IPV

Recent:

Previous:
Figure 4: A Quick Look at Employment Consequen

458 Victims

2.9%

N=13

Incomplete

Known

Status

N

97.1%

=445

Not Employed

32.1%

N=140

Not Employed

79.5%

N=111

Employed

20.6%

N=29

Employed

67

N

.9%

=305

Not

Employed

10.4%

N=30

Employed

89

N=2

.6%

75

At First Incident At Following 

Note: Ns are from unweighted frequencies; 

percentages are weighted.
Figure 5: Relative Risk Ratios of Victimization on Marital Dissolution/Reside

Mobility Among Married Women

0.2500.4500.6500.8501.0501.2501.4501.6501.8502.0502.250

Marital Dissolution vs.

Staying in the Home

Individual Move vs.

Staying in the Home

Household Move vs.

Staying in the Home

Marital Dissolution or

Individual Move vs.

Staying in the Home

Hous

Stayi

Relative Risk Ratio

Recent Intimate Partner ViolencePrevious Intimate Partner ViolenceRecent Nonviolent Crime VictimizationPrevious Nonviolent Crime Victimization

-----------------------------All Married Women----------------------- -----All Married Violent Crim

--
Researchers Sample

Type of Report (Past 6 months, Past Year, Lifetime, etc.) Study Design/ Methods Prevalence Findings

Klaus and Rand (1984) 1973-1981 National Crime Survey Past 6 Months Crime Survey Average yearly victimization r

violence perpetrated by a spouOverall rate: 0.15% (0.02% fofor women).

Morse (1995) 1983, 1986, 1989 and 1992 waves of the 

National Youth Survey (longitudinal)

Preceeding 12 Months "Structured, face-to-face, 

confidential interviews"

Percent of married or cohabitireporting any couple violence: age=18-24): 54.5% (Male PerpFemale Perpetrated: 48.0%) , iage=21-27): 45.9% (Male PerpFemale Perpetrated: 41.4%), in age=24-30): 39.8% (Male PerFemale Perpetrated: 35.0%), in age=27-33): 32.4% (Male PerpFemale Perpetrated: 27.9%). 

Rennison (2003)a 2001 National Crime Victimization Survey Past 6 Months Crime Survey 0.3% of U.S. population aged 

least one incident of intimate p0.5% of women and 0.09% of 

Straus, et al. (Straus and Gelles 1990b)

1975 National Family Violence Survey (2,146 Adults)

Past Year 16.0% of married/cohabiting c

violence; 12.1% of husbands w11.6% of wives were violent.

Straus and Gelles (1990a) b 1985 National Family Violence Resurvey (6,002 

Households)

Past Year Conflict Tactics Scale 15.8% of married/cohabiting c

violence; 11.3% of husbands w12.1% of wives were violent.

Tjaden and Thoennes (2000b) 1995-1996 National Violence Against Women 

Survey: Nationally Representative Survey of 16,000 (8,000 men and 8,000 women)

Lifetime and past 12 months

Telephone Survey About "Personal Safety"

Lifetime: Nearly 25% of womraped/physically assaulted; Paof women, 0.9% of men rapedassaulted.

Zlotnick, et al. (1998) 1987-1988 Married/Cohabiting Respondents to 

the National Survey of Families and Households

Past Year Survey 3.2% of couples reported phys

without injury (3.4% of wome1.1% of couples reported physwith injury (1.6% of women, 0

Table 1: Previous Findings from Nationally Representative Samples on the Prevalence of Intimate Partner Violence

bRates presented for the 1985 survey are based upon computations by Straus and Gelles (1990) that are based upon a subsample that is comparable to the 1975 samp

Divorced/separated respondents are excluded as are cases from state, Black and Hispanic oversamples. Further cases of violence measured in 1985 but not 1975 are However, the rates for 1985 are similar without these exclusions: 16.1% of couples report any violence in the past year; 11.6% of husbands were violent as were 12

aRennison's report presents rates for 1993-2001. In 1993, the overall rate of intimate partner violence was 0.58% (0.16% of men and 0.98% of women reported viol

by an intimate. In 1994, the overall rate was 0.55% (0.17% for men and 0.91% for women). In 1995, the overall rate was 0.49% (0.11% for men and 0.85% for wooverall rate was 0.47% (0.14% for men and 0.78% for women). In 1997, the overall rate was 0.43% (0.10% for men and 0.75% for women). In 1998, the overall rat(0.15% for men and 0.78% for women). In 1999, the overall rate was 0.35% (0.11% for men and 0.58% for women). In 2000, the overall rate was 0.28% (0.08% fofor women). 
Outcome Categories of Key Predictors Sample M

Model 1: Marital Dissolution/Woman's Move/Household Move(/No change)

Marital Dissolution/Individual Move/Household Movet+1 = f (Recent 

and Prior Victimizationst Racet, Classt, Demographic 

Characteristicst, Interview Characteristicst, Incident Characteristicsa)

All Wives Living with their Husband at Time t

MR

Model 2: Individual or Household Move

Individual/Household Movet+1 = f (Recent and Prior 

Victimizationst, Racet, Classt, Demographic Characteristicst, 

Interview Characteristicst, Incident Characteristicsa)

All Unmarried Women at Time t

DH

Model 3: Entry into the Labor Force Entry into the Labor Forcet = f (Recent and Prior Victimizationst, 

Racet, Classt , Demographic Characteristicst, Interview 

Characteristicst, Incident Characteristicsa)

All Women Unmployed at Time t

DH

Model 4: Exit from the Labor Force Exit from the Labor Forcet = f (Recent and Prior Victimizationst, 

Racet, Classt, Demographic Characteristicst, Interview 

Characteristicst, Incident Characteristicsa)

All Women Employed at Time t

DH

Model 5: Subsequent Intimate Partner Violence

Subsequent Assaultt+1 =f (Race, Class, Demographic Characteristics, 

Interview Characteristics, Incident Characteristicsa)

All Intimate Partner Violence Victims from Time of First Victimization

DH

Note: Appendix C details each of the variables in the indicated categories.Table 2: Multivariate Models

aSeparate Models are run to assess the role of incident characteristics. These models are restricted to victims of violent crime and all 

from the time of first victimization are included.
Victimizations

Recent Intimate Partner Violence 1.190 N/A 1.540 ** 0.988 2.059 *

Previous Intimate Partner Violence 3.857 * N/A 0.995 1.411 1.679

Recent Violence by Other Known Offender 0.377 0.809 1.058 0.305 1.067

Previous Violence by Other Known Offender 1.212 1.197 0.920 1.005 0.974

Recent Violence by a Stranger 1.314 0.848 1.120 1.106 1.062

Previous Violence by a Stranger 1.097 0.776 0.656 0.693 0.653

Recent Nonviolent Crime Victimization 1.290 ** 1.148 1.027 1.548 # 0.437 *

Previous Nonviolent Crime Victimization 1.259 # 0.541 1.217 * 1.097 0.542 #

Intervening Variables

Self-Defense -- -- -- 0.472 2.168

Injury -- -- -- 0.920 0.696

Injured and Sought Medical Attention for Injuries -- -- -- 1.266 0.408

Victim Notified the Police -- -- -- 1.027 0.737

Demographic Characteristics

Age 0.969 *** 0.957 *** 0.976 *** 0.944 * 0.982

Race

White, non-Hispanic (Reference/Omitted Category) -- -- -- -- --

Black, non-Hispanic 1.154 0.962 0.711 *** 1.468 1.793

Hispanic 0.795 1.156 0.870 * 0.391 0.854

Asian, non-Hispanic 0.583 * 0.953 0.683 *** 8.012 N/A

Native American, non-Hispanic N/A 2.032 0.876 N/A 0.383

Race Missing 0.877 3.666 0.169 N/A N/A

Education

Less than 12 Years 1.146 1.202 1.071 2.936 # 3.691 #

12 Years (Reference/Omitted Category) -- -- -- -- --

More than 12 Years 0.824 # 1.021 1.323 *** 0.705 1.461

Education Missing 0.953 2.026 *** 1.301 *** 0.475 0.974

Household Income

Low Income 1.829 *** 1.763 ** 1.214 ** 2.421 0.728

High Income 0.818 0.674 # 1.111 2.361 # 2.223

Income Imputed 1.266 N/A N/A N/A N/A

Income Missing 1.064 1.269 0.876 # 1.327 1.744

Employed 1.795 *** 0.656 ** 0.941 1.507 1.508

Employed Imputed 0.461 0.753 0.651 N/A N/A

Employed Missing 1.439 1.448 1.480 N/A N/A

Attending School 1.237 1.672 * 0.829 # 0.532 0.339

Attending School Imputed 1.190 N/A 0.489 N/A N/A

Attending School Missing 1.844 N/A 2.762 ** N/A N/A

Tenure 0.999 * 0.998 # 0.996 *** 0.997 0.993 *

Tenure Imputed 1.428 2.482 1.232 N/A 95.107 **

Home Ownership 0.751 0.530 0.057 *** 0.240 0.260

Multiple Unit Dwelling 0.896 1.376 1.490 *** 0.568 3.367

Multiple Unit Dwelling Missing N/A N/A N/A N/A N/A

Public Housing 1.493 0.246 0.525 ** N/A 0.791

Public Housing Missing 1.169 2.214 # 3.888 *** 2.377 0.549

Urbanicity 1.050 1.467 * 1.279 *** 1.445 1.891

Household Composition

Lone Adult 9.171 *** N/A 1.923 *** 8.373 * 0.468

Many Adults 1.489 *** 6.586 *** 0.779 *** 1.772 1.262

Number of Children 1.071 1.019 1.038 # 0.896 1.448 *

Proportion of Prior Interviews Not Married 6.619 *** 2.335 * 1.196 1.565 1.560

Interview Characteristics

Interview Period 1.035 0.984 1.042 ** 1.260 # 1.085

Interview Conducted Via Proxy 1.595 4.953 *** 1.319 # 7.576 * N/A

Incident Characteristics

-- -- -- 0.923 1.087

Perpetrator Arrested -- -- -- 0.797 1.102

Weapon Use -- -- -- 0.626 0.430

Perpetrator Under Influence of Drugs/Alcohol -- -- -- 0.861 1.219

Series Incident -- -- -- 0.866 3.074

Sample Size (Woman-Interviews)

N/A indicates that the cell size was too small to produce reliable estimates.

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests

1272

Marital 

Dissolution vs. 

Staying in the 

Home

Individual Move 

vs. Staying in 

the Home

Household 

Move vs. 

Staying in the 

Home

Marital 

Dissolution or 

Individual Move 

vs. Staying in 

the Home

Household 

Move vs. 

Staying in the 

Home

62,010

Police Notification by Someone Other than the Victim

All Women Married at t

Table 3: Relative Risk Ratios from Multinomial Logistic Regression Models Predicting Marital Dissolution and Residential Mobility

All Violent Crime Victims Married at 
Table 4: Odds Ratios from Logistic Regression Models Predicting Individual or Household Moves

Victimizations

Recent Intimate Partner Violence 1.235 *** 1.301 **

Previous Intimate Partner Violence 1.000 1.098

Recent Violence by Other Known Offender 1.059 1.041

Previous Violence by Other Known Offender 1.151 # 1.201

Recent Violence by a Stranger 1.196 * 1.164

Previous Violence by a Stranger 1.533 ** 1.573 **

Recent Nonviolent Crime Victimization 1.071 * 1.022

Previous Nonviolent Crime Victimization 1.102 * 1.031

Intervening Variables

Self-Defense -- 1.060

Injury -- 1.268 #

Injured and Sought Medical Attention for Injuries -- 0.984

Victim Notified the Police -- 0.777 #

Demographic Characteristics

Age 0.979 *** 0.974 ***

Race

White, non-Hispanic (Reference/Omitted Category) -- --

Black, non-Hispanic 0.692 *** 0.654 **

Hispanic 0.835 *** 1.415 #

Asian, non-Hispanic 0.732 *** 0.350

Native American, non-Hispanic 1.486 * 3.703 ***

Race Missing 0.472 * N/A

Education

Less than 12 Years 0.907 # 1.209

12 Years (Reference/Omitted Category) -- --

More than 12 Years 1.053 1.392

Education Missing 1.174 *** 1.486

Household Income

Low Income 1.105 ** 1.111

High Income 1.021 1.005

Income Imputed N/A N/A

Income Missing 1.072 1.408 *

Employed 1.076 * 0.960

Employed Imputed 0.949 1.184

Employed Missing 0.322 *** 0.226 ***

Attending School 1.344 *** 1.455 *

Attending School Imputed 1.284 * 1.047

Attending School Missing 1.002 1.327

Tenure 0.997 *** 0.998

Tenure Imputed 1.303 0.785

Home Ownership 0.262 *** 0.245 ***

Multiple Unit Dwelling 1.218 *** 1.205

Multiple Unit Dwelling Missing 3.115 *** 1.194

Public Housing 0.678 *** 0.498 *

Public Housing Missing 2.145 *** 1.933 *

Urbanicity 0.945 0.770 #

Household Composition

Lone Adult 0.767 *** 0.738 *

Many Adults 1.370 *** 1.206

Number of Children 1.031 # 1.023

Proportion of Prior Interviews Married 0.984 0.368 #

Interview Characteristics

Interview Period 1.015 0.985

Interview Conducted Via Proxy 1.303 *** 0.885

Incident Characteristics

-- 1.135

Perpetrator Arrested -- 0.841

Weapon Use -- 1.177

Perpetrator Under Influence of Drugs/Alcohol -- 0.946

Series Incident -- 0.613

Sample Size (Woman-Interviews)

N/A indicates that the cell size was too small to produce reliable estimates.

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests

62,182 3,072

Police Notification by Someone Other than the Victim

All Violent 

Crime Victims 

All Women 

Unmarried at t

Moving vs. 

Staying in the 

Home

Moving vs. 

Staying in the 

Home
Victimizations

Recent Intimate Partner Violence 0.868 1.422 #

Previous Intimate Partner Violence 1.031 1.115

Recent Violence by Other Known Offender 0.617 *** 0.967

Previous Violence by Other Known Offender 1.042 1.491

Recent Violence by a Stranger 0.439 *** 0.949

Previous Violence by a Stranger 1.024 3.177 #

Recent Nonviolent Crime Victimization 0.489 *** 0.850

Previous Nonviolent Crime Victimization 1.026 1.094

Intervening Variables

Self-Defense -- 1.212

Injury -- 0.754

Injured and Sought Medical Attention for Injuries -- 2.954 **

Victim Notified the Police -- 0.779

Demographic Characteristics

Age 0.953 *** 0.952 ***

Race

White, non-Hispanic (Reference/Omitted Category) -- --

Black, non-Hispanic 1.001 0.468 *

Hispanic 0.885 * 0.566

Asian, non-Hispanic 0.556 *** N/A

Native American, non-Hispanic 1.231 3.491 *

Race Missing 0.918 7.964 *

Education

Less than 12 Years 0.724 *** 0.764

12 Years (Reference/Omitted Category) -- --

More than 12 Years 1.224 *** 1.750

Education Missing 1.329 *** 2.217 *

Household Income

Low Income 0.676 *** 0.312 ***

High Income 1.033 1.705

Income Imputed 1.338 # N/A

Income Missing 0.976

Marital Status

Married 0.904 * 0.576

Divorced 1.472 *** 1.487

Single (Reference/Omitted Category) -- --

Marital Status Imputed 1.052 N/A

Marital Status Missing 0.708 N/A

Attending School 0.891 * 1.260

Attending School Imputed 0.708 2.502

Attending School Missing 1.007 0.784

Tenure 0.999 *** 0.999

Tenure Imputed 0.266 N/A

Home Ownership 0.893 0.851

Multiple Unit Dwelling 1.085 # 1.531

Multiple Unit Dwelling Missing 1.134 N/A

Public Housing 0.802 * 1.141

Public Housing Missing 0.979 1.418

Urbanicity 1.015 0.990

Household Composition

Lone Adult 0.929 0.746

Many Adults 1.203 *** 0.749

Number of Children 0.853 *** 1.090

Proportion of Prior Interviews Employed 30.416 *** 2.454 *

Interview Characteristics

Interview Period 0.879 *** 0.861 *

Interview Conducted Via Proxy 0.636 *** 0.724

Incident Characteristics

-- 1.018

Perpetrator Arrested -- 0.987

Weapon Use -- 0.974

Perpetrator Under Influence of Drugs/Alcohol -- 1.119

Series Incident -- 0.023 **

Sample Size (Woman-Interviews) 45,704 769.000

N/A indicates that the cell size was too small to produce reliable estimates.

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests

Police Notification by Someone Other than the Victim

All Women Not 

Employed at t

Table 5: Odds Ratios from Stacked Logistic Regression Models Predicting Labor Force Entry

All Victims Not 

Employed at t
Victimizations

Recent Intimate Partner Violence 0.913 0.889

Previous Intimate Partner Violence 0.925 1.092

Recent Violence by Other Known Offender 1.001 1.108

Previous Violence by Other Known Offender 1.046 1.053

Recent Violence by a Stranger 0.957 1.034

Previous Violence by a Stranger 0.955 0.501

Recent Nonviolent Crime Victimization 0.748 *** 1.118

Previous Nonviolent Crime Victimization 1.125 ** 1.039

Intervening Variables

Self-Defense -- 1.272

Injury -- 0.849

Injured and Sought Medical Attention for Injuries -- 1.051

Victim Notified the Police -- 0.943

Demographic Characteristics

Age 1.011 *** 0.966 **

Race

White, non-Hispanic (Reference/Omitted Category) -- --

Black, non-Hispanic 0.921 # 0.762

Hispanic 1.085 1.195

Asian, non-Hispanic 0.955 N/A

Native American, non-Hispanic 1.458 # 2.704

Race Missing 1.306 N/A

Education

Less than 12 Years 1.492 *** 1.405

12 Years (Reference/Omitted Category) -- --

More than 12 Years 0.888 ** 1.148

Education Missing 1.351 *** 1.721 *

Household Income

Low Income 1.665 *** 2.711 ***

High Income 1.004 0.551

Income Imputed 1.081 N/A

Income Missing 1.168 *** 1.324

Marital Status

Married 0.966 0.854

Divorced 0.655 *** 0.635 #

Single -- --

Marital Status Imputed 1.309 N/A

Marital Status Missing 0.811 N/A

Attending School 1.509 *** 0.729

Attending School Imputed 0.972 N/A

Attending School Missing 1.678 * 0.714

Tenure 1.001 *** 1.001

Tenure Imputed 0.584 N/A

Home Ownership 0.860 0.718

Multiple Unit Dwelling 0.997 0.950

Multiple Unit Dwelling Missing 2.454 N/A

Public Housing 1.445 *** 1.253

Public Housing Missing 1.011 1.106

Urbanicity 1.006 1.122

Household Composition

Lone Adult 0.772 *** 0.668

Many Adults 0.949 # 0.919

Number of Children 1.192 *** 1.303 **

Proportion of Prior Interviews Not Employed 12.117 *** 2.306 **

Interview Characteristics

Interview Period 0.909 *** 0.987

Interview Conducted Via Proxy 1.965 *** 4.638 *

Incident Characteristics

-- 1.048

Perpetrator Arrested -- 1.012

Weapon Use -- 1.743 **

Perpetrator Under Influence of Drugs/Alcohol -- 1.327

Series Incident -- 0.667

Sample Size (Woman-Interviews) 55,310 1493.000

N/A indicates that the cell size was too small to produce reliable estimates.

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests

Police Notification by Someone Other than the Victim

All Women 

Employed at t

Table 6: Odds Ratios from Stacked Logistic Regression Models Predicting Labor Force Exit

All Victims 

Employed at t
Table 7: Characteristics Associated with Intimate Partner Assault Report(s) (Weighted)

One Assault

First of Multiple 

Assaults

Number of Victims (Unweighted) 343 115

Percent of Victims 75.2% 24.9%

Self-defense 10.5% 14.4%

Injury 47.5% 50.1%

Injured and Sought Medical Attention for Injuries 9.3% 11.6%

Police Contact 50.3% 39.1% *

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests
Victimizations

Previous Intimate Partner Violence 0.253 ***

Recent Violence by Other Known Offender 1.063

Previous Violence by Other Known Offender 4.267 #

Recent Violence by a Stranger 1.618

Previous Violence by a Stranger 6.434

Recent Nonviolent Crime Victimization 1.749 ***

Previous Nonviolent Crime Victimization 0.963

Intervening Variables

Self-Defense 1.904 #

Injury 1.291

Injured and Sought Medical Attention for Injuries 1.641

Victim Notified the Police 1.142

Employment Consequences

Entered the Labor Force 0.961

Entered the Labor Force Missing N/A

Left the Labor Force 0.311 #

Left the Labor Force Missing N/A

Marital Dissolution 1.557

Marital Dissolution Missing N/A

Demographic Characteristics

Age 0.956 **

Race

White, non-Hispanic (Reference/Omitted Category) --

Black, non-Hispanic 0.402 *

Hispanic 2.405 *

Asian, non-Hispanic N/A

Native American, non-Hispanic 0.917

Race Missing N/A

Education

Less than 12 Years 0.956

12 Years (Reference/Omitted Category) --

More than 12 Years 0.991

Education Missing 2.966 **

Household Income

Low Income 0.766

High Income 0.564

Income Imputed N/A

Income Missing 0.283 **

Marital Status

Married 1.332

Divorced 1.651

Single --

Marital Status Imputed N/A

Marital Status Missing N/A

Employed 0.807

Employed Imputed N/A

Employed Missing 0.374

Attending School 1.412

Attending School Imputed N/A

Attending School Missing 2.080

Tenure 1.002

Tenure Imputed 1.534

Home Ownership 0.732

Multiple Unit Dwelling 1.583

Multiple Unit Dwelling Missing 0.979

Public Housing 3.015 #

Public Housing Missing 2.414

Urbanicity 0.841

Household Composition

Lone Adult 1.158

Many Adults 1.944 *

Number of Children 0.781 #

Interview Characteristics

Interview Period 0.773 **

Interview Conducted Via Proxy N/A

Unbounded Interview 4.719 ***

Prior IPV Incident Characteristics

0.480 #

Perpetrator Arrested 0.414 *

Weapon Use 0.426 *

Perpetrator Under Influence of Drugs/Alcohol 2.647 ***

Series Incident 173.827 ***

Offender Acted Before 0.231 ***

Sample Size (Woman-Interviews) 1,118

N/A indicates that the cell size was too small to produce reliable estimates.

#p<0.10, *p<0.05, **p<0.01, ***p<0.001, two-tailed tests

Police Notification by Someone Other than the Victim

Table 8: Odds Ratios from Stacked Logistic Regression Models Predicting Subsequent Intimate Partner Assault