Mixed-effects nonlinear regression for unbalanced repeated measures

E. F. Vonesh, R. L. Carter

Research output: Contribution to journalArticlepeer-review

177 Scopus citations

Abstract

Repeated measures data, such as clinical pharmacokinetic data, growth data, and dose-response data, are often inherently nonlinear with respect to a given response function and are frequently incomplete and/or unbalanced. Nonlinear random-effects models together with a variety of estimation procedures have been proposed for the analysis of such data. This paper is concerned with a straightforward procedure for estimating and comparing the parameters of a generalized mixed-effects nonlinear regression model. The asymptotic properties of the proposed estimators are given and large-sample tests of hypotheses provided. The results are applied to in vitro data on the water transport kinetics of hemodialyzers used in the treatment of patients with chronic renal failure.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalBiometrics
Volume48
Issue number1
DOIs
StatePublished - Jan 1 1992

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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