We consider maximum likelihood (ML) estimation of mean and covariance structure models when data are missing. Expectation maximization (EM), generalized expectation maximization (GEM), Fletcher-Powell, and Fisher-scoring algorithms are described for parameter estimation. It is shown how the...

Using explicit formulas for the information matrix of ML factor analysis under multivariate normal theory, gross and net information for estimating the parameters in a covariance structure gained by adding the associated mean structure are defined. It is proved that a necessary and sufficient...