Want to analyze hierarchical data with binary outcomes? This comprehensive review examines the use of multilevel logit models in sociological research over the past decade. It provides a structured overview of studies employing these models, focusing on the hypotheses tested, the hierarchical data structures analyzed, and the multilevel data sources used. It also contains two examples on multilevel models for binary outcomes. This paper is structured to assist researchers in effectively working with multilevel models for binary outcomes, including model conceptualization, model description for research, understanding multilevel data structures, model estimation, and result interpretation. The approach emphasizes the need to correctly understand the multilevel data, thus it's designed to assist. Ultimately, these examples provide a framework for researchers to effectively analyze complex data sets. This resource offers valuable guidance for sociologists and other social scientists seeking to apply multilevel modeling techniques to their research.
This review, appearing in the Annual Review of Sociology, directly aligns with the journal's mission to provide comprehensive overviews of significant developments in sociological research. By examining the application of multilevel models, the paper offers valuable insights for sociologists working with complex, hierarchical data. The context of this research contributes significantly to the journal's core focus.