Types of change: Application of configural frequency analysis in repeated measurement designs

Abstract

Many researchers are concerned both with intraindividual change patterns and interindividual differences and similarities in those change patterns. Configural Frequency Analysis (CFA) provides a way to identify overrepresentations (types) and under-representations (antitypes) in the frequencies of multiple variable classifications organized to reflect patterns of change. Three methods of CFA for analyzing repeated measures data are considered. To establish trends, two of them require at least ordinal data and the third requires interval data. Data analysis and the interpretation of results are illustrated. CFA is compared with residual analysis from log-linear modeling.