This paper considers the large sample behavior of the maximum likelihood estimator of random effects models with serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. Consistent estimation and asymptotic normality as N and/or T grows large is established...

This paper is concerned with maximum likelihood based inference in random effects models with serial correlation. Allowing for individual effects we introduce serial correlation of general form in the time effects as well as the idiosyncratic errors. A straightforward maximum likelihood...

This paper deals with the question how to model health effects after the cessation of a randomised controlled trial (RCT). Using clinical trial data on severe congestive heart failure patients we illustrate how survival beyond the cessation of a RCT can be predicted based on parametric survival...