Maximum likelihood estimation for longitudinal data with truncated observations

We obtain maximum likelihood estimates of the parameters when the observations on the response variable in a repeated measures design are truncated above a cutpoint. The maximum likelihood equations are solved iteratively using an EM-like procedure. It is observed that these estimates have smaller mean squared error than recently proposed iterative weighted least-squares estimates. The results are applied to data arising from a study of dioxin elimination in Air Force veterans.