von Eye and Wiedermann present the General Linear Model (GLM) and derivatives such as correlation, regression, analysis of variance, and direction dependence analysis in a compact format. Each method is illustrated using real-world data so that students, instructors, and data analysts can understand methods and procedures.
Foundations, Models, and Applications
This unique book offers comprehensive coverage of configural frequency analysis (CFA), a key method for analyzing categorical data in person-oriented research. It presents the foundations, methods, and models of CFA, accompanied by numerous empirical data examples across various disciplines that readers can reproduce. The text also explores computer applications, including relevant R packages and modules. CFA is a statistical approach that addresses significant questions in categorical data, emphasizing patterns of variable categories in relation to specific hypotheses, enabling the testing of multiple substantive hypotheses. The book outlines the origins of CFA and its connection to chi-square analysis, alongside developments based on log-linear modeling. It discusses models ranging from simple variable independence to complex models for testing causal hypotheses, providing empirical examples for each. New models for person-oriented mediation analysis and locally optimized time series analysis are introduced, with findings supported by Monte Carlo simulations. Aimed primarily at researchers and students in the social and behavioral sciences, the book will also attract anyone working with categorical data from a person-centered perspective.
Person-oriented research is based on the fact that statements at the aggregate level rarely apply at the level of smaller numbers of cases or individuals. The first tenet of person-oriented research proposes that structure and development of behavior are, at least in part, specific to the individual. While aggregate-level statements may be correct, they cover only that portion of the overall variability that is shared by the aggregate. Larger, and more important portions of variability may remain unexplained. Recent research has already created many examples that show that individual characteristics may not be captured at all when results that were created at the aggregate level are used for description at the individual level. With this volume, we pursue three aims: provide an overview of theoretical and methodological developments of person-oriented research; present recent and new developments in the domain of statistical analysis of data from a person-oriented perspective; and, present empirical sample cases in which methodological implications of the relationship between aggregate-level and person-oriented research are defined and illustrated."