D. Bates

Publications132
h-index38
Citations85,492
Highly Influential Citations5,891
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Fitting Linear Mixed-Effects Models Using lme4
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most… Expand
Bioconductor: open software development for computational biology and bioinformatics
TLDR
Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described. Expand
Mixed-Effects Models in S and S-PLUS
Linear Mixed-Effects * Theory and Computational Methods for LME Models * Structure of Grouped Data * Fitting LME Models * Extending the Basic LME Model * Nonlinear Mixed-Effects * Theory and… Expand
Linear Mixed-Effects Models using 'Eigen' and S4
TLDR
The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen``glue''. Expand
Mixed-effects modeling with crossed random effects for subjects and items
This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent… Expand
Nonlinear Regression Analysis and Its Applications
TLDR
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. Expand
Nonlinear mixed effects models for repeated measures data.
TLDR
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. Expand
Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model
Abstract Nonlinear mixed-effects models have received a great deal of attention in the statistical literature in recent years because of the flexibility they offer in handling the unbalanced… Expand
fitting linear mixed effects models using lme 4 arxiv
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most… Expand
Relative Curvature Measures of Nonlinearity
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