Nonlinear Mixed Effects Models for Repeated Measures Data

1990/09/01 by Mary J. Lindstrom, Douglas M. Bates · 46 citations
Mathematics · #Statistical Methods and Bayesian Inference #Advanced Statistical Methods and Models #Statistical Methods and Inference

paper · doi:10.2307/2532087

Abstract

We propose a general, nonlinear mixed effects model for repeated measures data and define estimators for its parameters. The proposed estimators are a natural combination of least squares estimators for nonlinear fixed effects models and maximum likelihood (or restricted maximum likelihood) estimators for linear mixed effects models. We implement Newton-Raphson estimation using previously developed computational methods for nonlinear fixed effects models and for linear mixed effects models. Two examples are presented and the connections between this work and recent work on generalized linear mixed effects models are discussed.

Citations

• Longitudinal data analysis using generalized linear models

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