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 Louis’s method. The methodology is illustrated with numerical simulations.

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