This article combines procedures for single-level mediational analysis with multilevel modeling techniques in order to appropriately test mediational effects in clustered data. A simulation study compared the performance of these multilevel mediational models with that of single-level mediational models in clustered data with individual-or group-level initial independent variables, individual-or group-level mediators, and individual level outcomes. The standard errors of mediated effects from the multilevel solution were generally accurate, while those from the single-level procedure were downwardly biased, often by 20% or more. The multilevel advantage was greatest in those situations involving group-level variables, larger group sizes, and higher intraclass correlations in mediator and outcome variables. Multilevel mediational modeling methods were also applied to data from a preventive intervention designed to reduce intentions to use steroids among players on high school football teams. This example illustrates differences between single-level and multilevel mediational modeling in real-world clustered data and shows how the multilevel technique may lead to more accurate results.

Six studies examined the role of positive affect (PA) in the experience of meaning in life (MIL). Study 1 showed strong relations between measures of mood, goal appraisals, and MIL. In multivariate analyses, PA was a stronger predictor of MIL than goal appraisals. In Study 2, the most consistent predictor of the experience of meaning in a day was the PA experienced that day. Later, global MIL was predicted by average daily PA, rather than average daily MIL. Study 3 demonstrated no prospective relations between measures of MIL and PA over 2 years. In Study 4, priming positive mood concepts enhanced MIL. In Study 5, manipulated positive mood enhanced ratings of MIL for those who were not given an attributional cue for their moods. In Study 6, PA was associated with a high level of distinction between meaningful and meaningless activities. Results indicate that positive moods may predispose individuals to feel that life is meaningful. In addition, positive moods may increase sensitivity to the meaning-relevance of a situation.

Theories hypothesizing interactions between a categorical and one or more continuous variables are common in personality research. Traditionally, such hypotheses have been tested using nonoptimal adaptations of analysis of variance (ANOVA). This article describes an alternative multiple regression-based approach that has greater power and protects against spurious conclusions concerning the impact of individual predictors on the outcome in the presence of interactions. We discuss the structuring of the regression equation, the selection of a coding system for the categorical variable, and the importance of centering the continuous variable. We present in detail the interpretation of the effects of both individual predictors and their interactions as a function of the coding system selected for the categorical variable. We illustrate two- and three-dimensional graphical displays of the results and present methods for conducting post hoc tests following a significant interaction. The application of multiple regression techniques is illustrated through the analysis of two data sets. We show how multiple regression can produce all of the information provided by traditional but less optimal ANOVA procedures.

Most prevention programs are based on theory of individual behavior. Consequently, the success of a prevention program is measured by its effect on individuals. Often, however, individuals are clustered within intact groups, and for practical reasons, the prevention intervention is randomized and administered at the group level. The groups involved in such a design may include classes or schools in educational contexts, hospitals or other treatment sites in clinical contexts, companies or offices in organizational contexts, and neighborhoods, counties, states, or countries in geographical contexts. When intact groups are assigned to conditions and observations are made on individuals within these groups, a multilevel data set is formed. The independent variable, assignment to intervention or control condition, is a group level variable, and the dependent variable is measured at the individual

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Using data from a biracial community sample of adolescents, the present study examined trajectories of alcohol use and abuse over a 15-year period, from adolescence into young adulthood, as well as the extent to which these trajectories were differentially predicted by coping and enhancement motives for alcohol use among the 2 groups. Coping and enhancement motivations (M. L. Cooper, 1994) refer to the strategic use of alcohol to regulate negative and positive emotions, respectively. Results showed that Black and White youth follow distinct alcohol trajectories from adolescence into young adulthood and that these trajectories are differentially rooted in the regulation of negative and positive emotions. Among Black drinkers, coping motives assessed in adolescence more strongly forecast differences in alcohol involvement into their early 30s, whereas enhancement motives more strongly forecast differences among White drinkers. Results of the present study suggest that different models may be needed to account for drinking behavior among Blacks and Whites and that different approaches may prove maximally effective in reducing heavy or problem drinking among the 2 groups.

These results extend prior findings, supporting the effectiveness and efficiency of a modular, multifocus approach that incorporates monitoring and feedback relative to community implementation of evidence-based treatments. (PsycINFO Database Record

Many college entrants’ parents do not have college degrees. These entrants are at high risk for attrition, suggesting it is critical to understand mechanisms of attrition relative to parental education. Moderators and mediators of the effect of parental education on attrition were investigated in 3,290 students over 4 years. Low parental education was a risk for attrition; importantly, college GPAs both moderated and mediated this effect, and ACT scores, scholarships, loans, and full-time work mediated this effect. Drug use, psychological distress, and few reported academic challenges predicted attrition, independent of parental education. These findings might inform interventions to decrease attrition.