Logistic regression analyses were used to assess the association between victimization from mental and physical bullying and use of alcohol, cigarettes, marijuana, and inhalants among middle school students. Self-report data were analyzed from 926 ethnically diverse sixth through eighth grade students (43% white, 26% Latino, 7% Asian American/Pacific Islander, 3% African American, 14% mixed ethnic origin, and 5% "other") ages 11 -14 years from southern California. Substance use was collected at two time points (fall 2004 and spring 2005) during an academic year. Models were run for each substance separately. Results supported an association between victimization from bullying and substance use. Youths who experienced each type of bullying (mental or physical) separately or in combination were more likely to report use of each substance in spring 2005. This finding held after controlling for gender, grade level, ethnicity and substance use in fall 2004. Keywordsbullying; substance use; adolescents; victimization During the middle school years (grades 6 -8), an increasing number of youths become the victims of bullying (e.g., Espelage, Bosworth & Simon, 2001), or repeated "intentional physical and psychological harm" (Smith & Thompson, 1991, p. 1). Bullying can include verbal or written name-calling, teasing, and threats, social exclusion, and hitting, kicking, or other violent bodily contact (Espelage et al., 2001). Bullying can negatively affect concentration, self-esteem and social relationships in school, and promote feelings of isolation and hopelessness, often with long-term consequences that lead into adulthood (Batsche & Knoff, 1994;Kaltiala-Heino, Rimpela, Marttunen, Rimpela, & Rantanen, 1999;Olweus, 1993). National statistics on the incidence of victimization from bullying indicate that bullying is a significant problem. Finkelhor, Ormrod, Turner, and Hamby (2005) sampled a nationally * Corresponding Author. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. representative group of children between the ages of 2 -17 and found that 50% of their sample had experienced bullying, which they termed emotional bullying or teasing. In earlier work that focused directly on school aged children, Nansel et al. (2001) found that 10.6% of students in grades 6 through 10 in the United States reported being victims of bullying and another 6.3% reported being both victims and perpetrators. They defined bullying as when someone "[says or does] nasty and unpleasant things to him or her" or "when a student is teased repeatedly in a way he or she doesn't like." NIH Public Acce...

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This article reports on an extension of group-based trajectory modeling to address nonrandom participant attrition or truncation due to death that varies across trajectory groups. The effects of the model extension are explored in both simulated and real data. The analyses of simulated data establish that estimates of trajectory group size as measured by group membership probabilities can be badly biased by differential attrition rates across groups if the groups are initially not well separated. Differential attrition rates also imply that group sizes will change over time, which in turn has important implications for using the model parameter estimates to make population-level projections. Analyses of longitudinal data on disability levels in a sample of very elderly individuals support both of these conclusions.

In the U.S. college-educated women earn approximately 30 percent less than their non-Hispanic white male counterparts. We conduct an empirical examination of this wage disparity for four groups of women-non-Hispanic white, black, Hispanic, and Asian-using the National Survey of College Graduates, a large data set that provides unusually detailed information on higher-level education. Nonparametric matching analysis indicates that among men and women who speak English at home, between 44 and 73 percent of the gender wage gaps are accounted for by such pre-market factors as highest degree and major. When we restrict attention further to women who have "high labor force attachment" (i.e., work experience that is similar to male comparables) we account for 54 to 99 percent of gender wage gaps. Our nonparametric approach differs from familiar regression-based decompositions, so for the sake of comparison we conduct parametric analyses as well. Inferences drawn from these latter decompositions can be quite misleading.

Survey research on older adults, especially regarding racial/ethnic disparities in health care, could benefit from improved response rates. These results suggest that targeted prenotification materials and campaigns, tailored follow-up, targeted Spanish mailings, Chinese translations/calls, and adjustments to telephone protocols may improve representation and response.

Abstract-We estimate wage gaps using nonparametric matching methods and detailed measures of field of study for university graduates. We find a modest portion of the wage gap is the consequence of measurement error in the Census education measure. For Hispanic and Asian men, the remaining gap is attributable to premarket factors-primarily differences in formal education and English language proficiency. For black men, only about one-quarter of the wage gap is explained by these same factors. For a subsample of black men born outside the South to parents with some college education, these factors do account for the entire wage gap.

A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This article describes and applies a method for using observational longitudinal data to make more transparent causal inferences about the impact of such events on developmental trajectories. The method combines 2 distinct lines of research: work on the use of finite mixture modeling to analyze developmental trajectories and work on propensity score matching. The propensity scores are used to balance observed covariates and the trajectory groups are used to control pretreatment measures of response. The trajectory groups also aid in characterizing classes of subjects for which no good matches are available. The approach is demonstrated with an analysis of the impact of gang membership on violent delinquency based on data from a large longitudinal study conducted in Montréal, Canada.

Objective. Adjust for subgroup differences in extreme response tendency (ERT) in ratings of health care, which otherwise obscure disparities in patient experience. Data Source. 117,102 respondents to the 2004 Consumer Assessment of Healthcare Providers and Systems (CAHPS) Medicare Fee-for-Service survey. Study Design. Multinomial logistic regression is used to model respondents' use of extremes of the 0-10 CAHPS rating scales as a function of education. A new two-stage model adjusts for both standard case-mix effects and ERT. Ratings of subgroups are compared after these adjustments. Principal Findings. Medicare beneficiaries with greater educational attainment are less likely to use both extremes of the 0-10 rating scale than those with less attainment. Adjustments from the two-stage model may differ substantially from standard adjustments and resolve or attenuate several counterintuitive findings in subgroup comparisons. Conclusions. Addressing ERT may be important when estimating disparities or comparing providers if patient populations differ markedly in educational attainment. Failures to do so may result in misdirected resources for reducing disparities and inaccurate assessment of some providers. Depending upon the application, ERT may be addressed by the two-stage approach developed here or through specified categorical or stratified reporting.