Configural Frequency Analysis

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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.