To complement recent articles in this journal on structural equation modeling (SEM) practice and principles by Martens and by Quintana and Maxwell, respectively, the authors offer a consumer’s guide to SEM. Using an example derived from theory and research on vocational psychology, the authors outline six steps in SEM: model specification, identification, data preparation and screening, estimation, evaluation of fit, and modification. In addition, the authors summarize the debates surrounding some aspects of SEM (e.g., acceptable sample size, fit indices), with recommendations for application. They also discuss the need for considering and testing alternative models and present an example, with details on determining whether alternative models result in a significant improvement in fit to the observed data.

Likert-type scales are commonly used when assessing attitudes, personality characteristics, and other psychological variables. This study examined the effect of varying the number of response options on the same set of 28 attitudinal items. Participants answered items using either a 4-point scale (forced choice), a 5-point scale that included a "neither" mid-point, or a 4-point scale with an option of "no opinion" presented after the item. The questionnaire also included an item asking participants what they believe the midpoint in a scale indicated. As predicted, participants' interpretations of the midpoint varied widely with the most common responses being: "no opinion," "don't care," "unsure," "neutral," "equal/both," and "neither." The quantitative results showed that participants' levels of item endorsement varied based on the response options offered. For example, "neither" was chosen more often than "no opinion" on all of the items.

Objective: To provide an overview of structural equation modeling (SEM) using an example drawn from the rehabilitation psychology literature. Design: To illustrate the 5 steps in SEM (model specification, identification, estimation methods, interpretation of results, and model modification), an example is presented, with details on determining whether alternataive models result in a significant improvement to fit to the observed data. Data are from a sample of 274 people with spinal cord injury. Issues commonly encountered in preparing data for SEM analyses (e.g., missing data, nonnormality) are reviewed, as is the debate surrounding some aspects of SEM (e.g., acceptable sample size). Conclusion: SEM can be a powerful procedure for empirically representing complex and sophisticated theoretical models of interest to rehabilitation psychologists.

Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 or 10 grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.

This study contrasted the effects of intimate partner and nonpartner sexual assault on women's mental health among a sample (N=835) of low-income, ethnically diverse community women. Compared to sexual assault by a previous partner or by a non-intimate partner, sexual assault by a current partner was the strongest predictor of PTSD, stress, and dissociation. Non-intimate partner sexual assault was only a significant predictor of PTSD and only for African American women. These findings suggest that the victim-offender relationship is important when considering the impact of sexual assault. Specifically, sexual assault perpetrated by an intimate partner may be especially traumatic.