Maximum likelihood estimation for longitudinal data with truncated observations

Kishan G. Mehrotra, Pandurang M. Kulkarni, Ram C. Tripathi, Joel E. Michalek

Research output: Contribution to journalArticle

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2975-2988
Number of pages14
JournalStatistics in Medicine
Volume19
Issue number21
DOIs
StatePublished - Nov 15 2000

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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