A factor mixture analysis model for multivariate binary data

作者：Cagnone Silvia; Viroli Cinzia^*

来源：Statistical Modelling, 2012, 12(3): 257-277.

DOI：10.1177/1471082X1101200303

• model based clustering
• latent trait analysis
• EM algorithm

The paper proposes a latent variable model for binary data coming from an unobserved heterogeneous population. The heterogeneity is taken into account by replacing the traditional assumption of Gaussian distributed factors by a finite mixture of multivariate Gaussians. The aim of the proposed model is twofold: it allows to achieve dimension reduction when the data are dichotomous and, simultaneously, it performs model based clustering in the latent space. Model estimation is obtained by means of a maximum likelihood method via a generalized version of the EM algorithm. In order to evaluate the performance of the model a simulation study and two real applications are illustrated.

• 出版日期2012-6