Configural Frequency Analysis (eBook)

This unique book provides a comprehensive and detailed coverage of configural frequency analysis (CFA), the most useful method of analysis of categorical data in person-oriented research. It presents the foundations, methods, and models of CFA and features numerous empirical data examples from a range of disciplines that can be reproduced by the readers. It also addresses computer applications, including relevant R packages and modules.

Configural frequency analysis is a statistical method that allows the processing of important and interesting questions in categorical data. The perspective of CFA differs from the usual perspective of relations among variables; its focus is on patterns of variable categories that stand out with respect to specific hypotheses, and as such, CFA allows for testing numerous substantive hypotheses.

The book describes the origins of CFA and their relation to chi-square analysis as well as the developments that are based on log-linear modeling. The models covered range from simple models of variable independence to complex models that are needed when causal hypotheses are tested. Empirical data examples are provided for each model. New models are introduced for person-oriented mediation analysis and locally optimized time series analysis, and new results concerning the characteristics of CFA methods are bolstered using Monte Carlo simulations.

Alexander von Eye is Professor Emeritus of Psychology at the Department of Psychology at Michigan State University in East Lansing, MI, USA. His primary research interests include the development and application of methods for the analysis of categorical and longitudinal data, computer simulations, and developmental research. He is also concerned with the theory of person-oriented research and with the development of methods for causal research. He has published numerous books, mostly on topics of applied statistics, and he is the author of over 400 articles in scholarly journals.

Wolfgang Wiedermann is an Associate Professor of Quantitative Methods at the Department of Educational, School & Counseling Psychology and the Missouri Prevention Science Institute at the University of Missouri, Columbia, MO, USA. His primary research interests include the development of methods for causal inference, methods to determine the direction of causal dependence, and methods for person-oriented research settings. He has edited books on statistical methods for causal inference and new developments in statistical methods for dependent data analysis in the social and behavioral sciences.