[Configuration cluster analysis as an alternative to configuration frequency analysis]

The paper discusses configural cluster analysis (CCA) as an alternative to configural frequency analysis (CFA). CFA defines types as deviations from the assumption of no interactions among the variables. CCA defines clusters as deviations from the stronger assumption of a total lack of effects, in the contingency table. Variations of CCA as aggregating CCA, hierarchical CCA, m-sample CCA, and CCA of profile shifts are discussed. An example analyzes data from research on depression.