Mixed mode data clustering: an approach based on tetrachoric correlations

In this paper we face the problem of clustering mixedmode data by assuming that the observed binary variables aregenerated from latent continuous variables. We perform a principalcomponents analysis on the matrix of tetrachoric correlations andwe estimate the scores of each latent variable and reach a datamatrix with continuous variables to be used in fully Guassianmodels or in the k-means cluster analysis. Results on a simulationstudy and on a real data set are reporte