We review some of the work of the past ten years that applied the multilevel logit model. We attempt to provide a brief description of the hypothesis tested, the hierarchical data structure analyzed, and the multilevel data source for each piece of work we have reviewed. We have also reviewed the technical literature and worked out two examples on multilevel models for binary outcomes. The review and examples serve two purposes: First, they are designed to assist in all aspects of working with multilevel models for binary outcomes, including model conceptualization, model description for a research report, understanding of the structure of required multilevel data, estimation of the model via a generally available statistical package, and interpretation of the results. Second, our examples contribute to the evaluation of the approximation procedures for binary multilevel models that have been implemented for general public use.

Although adverse consequences of poverty for children are documented widely, little is understood about the mechanisms through which the effects of poverty disadvantage young children. In this analysis we investigate multiple mechanisms through which poverty affects a child's intellectual development. Using data from the NLSY and structural equation models, we have constructed five latent factors (cognitive stimulation, parenting style, physical environment, child's ill health at birth, and ill health in childhood) and have allowed these factors, along with child care, to mediate the effects of poverty and other exogenous variables. We produce two main findings. First, the influence of family poverty on children's intellectual development is mediated completely by the intervening mechanisms measured by our latent factors. Second, our analysis points to cognitive stimulation in the home, and (to a lesser extent) to parenting style, physical environment of the home, and poor child health at birth, as mediating factors that are affected by lack of income and that influence children's intellectual development.

Exposure to sexual content in music, movies, television, and magazines accelerates white adolescents' sexual activity and increases their risk of engaging in early sexual intercourse. Black teens appear more influenced by perceptions of their parents' expectations and their friends' sexual behavior than by what they see and hear in the media.

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This study, drawing on approximately 1,100 males from the National Longitudinal Study of Adolescent Health, demonstrates the importance of genetics, and genetic-environmental interactions, for understanding adolescent delinquency and violence. Our analyses show that three genetic polymorphisms—specifically, the 30-bp promoter-region variable number tandem repeat (VNTR) in MAOA, the 40-bp VNTR in DAT1, and the Taq1 polymorphism in DRD2—are significant predictors of serious and violent delinquency when added to a social-control model of delinquency. Importantly, findings also show that the genetic effects of DRD2 and MAOA are conditional and interact with family processes, school processes, and friendship networks. These results, which are among the first that link molecular genetic variants to delinquency, significantly expand our understanding of delinquent and violent behavior, and they highlight the need to simultaneously consider their social and genetic origins.