Maximum likelihood estimation for joint mean–covariance models from unbalanced repeated-measures data

This paper develops maximum likelihood estimates for jointly modelling the mean and covariance matrix, for unbalanced repeated measures, using an unconstrained parametrization. Furthermore, the asymptotic distribution of the estimated parameters and the results of a simulation study are presented.