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Maximum likelihood estimation for longitudinal data with truncated observations
K G Mehrotra1, P M Kulkarni, R C Tripathi
1Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY 13224, USA.
Statistics in Medicine
|October 24, 2000
Abstract:
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. Published in 2000 by John Wiley & Sons, Ltd.