Analysis of multivariate polychoric correlation models with incomplete data

Several methods of analysing the multivariate polychoric correlation model with missing data are studied. They are the direct maximum likelihood method, the partition maximum likelihood method, the complete data method, the mean replacement method, the regression replacement method and the principal components method. Based on results of some simulation studies, the direct maximum likelihood method and the partition maximum likelihood method are recommended.