Maximum likelihood estimation of multinomial probit factor analysis models for multivariate t-distribution
We propose a model for multinomial probit factor analysis by assuming t-distribution error in probit factor analysis. To obtain maximum likelihood estimation, we use the Monte Carlo expectation maximization algorithm with its M-step greatly simplified under conditional maximization and its E-step made feasible by Monte Carlo simulation. Standard errors are calculated by using Louiss method. The methodology is illustrated with numerical simulations.
factor analysis t-distribution multinomial probit model mcem algorithm