D
Douglas M. Bates
Researcher at University of Wisconsin-Madison
Publications - 80
Citations - 117051
Douglas M. Bates is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Generalized linear mixed model & Random effects model. The author has an hindex of 36, co-authored 80 publications receiving 88022 citations. Previous affiliations of Douglas M. Bates include Kansas State University & University of Alberta.
Papers
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Journal ArticleDOI
Mixed-effects modeling with crossed random effects for subjects and items
TL;DR: In this article, the authors provide an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects, and a worked-out example of how to use recent software for mixed effects modeling is provided.
Book
Nonlinear Regression Analysis and Its Applications
Douglas M. Bates,Donald G. Watts +1 more
TL;DR: This book offers a balanced presentation of the theoretical, practical, and computational aspects of nonlinear regression and provides background material on linear regression, including the geometrical development for linear and nonlinear least squares.
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Nonlinear Mixed Effects Models for Repeated Measures Data
TL;DR: A general, nonlinear mixed effects model for repeated measures data and define estimators for its parameters are proposed and Newton-Raphson estimation is implemented using previously developed computational methods for nonlinear fixed effects models and for linear mixed effects models.
Journal ArticleDOI
Linear and nonlinear mixed-effects models
TL;DR: It is shown how the concept of a random coefficient model can be extended to nonlinear models so as to fit nonlinear mixed-effects models, and how this can be used in a variety of situations.
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Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model
TL;DR: In this paper, the authors consider four different approximations to the log-likelihood, comparing their computational and statistical properties, and conclude that the linear mixed-effects (LME) approximation suggested by Lindstrom and Bates, t