Abstract:

Factor Mixture Model (FMM) is a factor analysis model in which the latent population heterogeneity is considered. Combined with latent class analysis (LCA) and traditional factor analysis (FA), the FMM model consistently preserves the advantages of these two statistical methods, and has some unique features as well. Present empirical applications of FMM include the description of latent structure of variables, classification of subjects, and detection of social desirability bias. We suggest to fit data with FA, LCA and FMM respectively, and to choose an optimal model according to the fit indexes and practical implications. By applying FMM to build the measurement model of consciousness of social face, we illustrate the analysis steps and software operation procedures. Future research efforts are needed for some issues on FMM, such as the simplification of analytical process and the selection of fit index.

Key words: factor mixture model, latent class analysis, factor analysis