mean mixture normal factor analysis for handling missing data

This paper presents an extension of the factor analysis model based on themean mixture normal in the presence of nonresponses and missing data. missing datamay occur due to operator error or incomplete data capturing therefore they cannotbe ignored in factor analysis modeling. we implement an em-type algorithm for maximumlikelihood estimation and propose single imputation of possible missing valuesunder a missing at random mechanism.