Heteroscedastic nonlinear regression models with random effects
Loading...
Date
1998
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Universitätsbibliothek Dortmund
Abstract
We discuss an extansion of the nonlinear random effects model from Lindstrom and Bates (1990) by adding a flexible transformation to both sides of the model (see Carroll and Ruppert (1988)) and describe a procedure for parameter estimation. This method combines pseudo maximum likelihood estimators for the transform-both-sides and weighting model and maximum likelihood (or restricted maximum likelihood) estimatiors for the linear mixed effects models. A validation of this new method is performed by analyzing a simulated set of enzyme kinetic data published by Jones (1993).
Description
Table of contents
Keywords
enzyme kinetics, nonlinear regression, Pseudo likelihood estimation, random effects, repeated measures data, transformation and weighting