`Mixed-Effects Models in S and S-PLUS'

by J. C. Pinheiro and D. M. Bates

Springer. ISBN 0-387-98957-9, 2000.

Hardback 232mm × 155mm, xvi+528 pages, US price $69.95

Full-size cover image (127

This is a comprehensive guide to the theory and applications of linear and nonlinear mixed-effects models and to the use of the nlme library for S-PLUS and R. It was published on 4 May 2000.

On-line material:
Description Contents Scripts and complements
Errata Contact authors Publisher's Web Sites

There are mirrors of this material at U. of Wisconsin and Bell Labs.


This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. A unified model-building strategy for both linear and nonlinear models is presented and applied to the analysis of over 20 real datasets from a wide variety of areas, including pharmacokinetics, agriculture, and manufacturing. A strong emphasis is placed on the use of graphical displays at the various phases of the model-building process, starting with exploratory plots of the data and concluding with diagnostic plots to assess the adequacy of a fitted model. Over 170 figures are included in the book.

The NLME library for analyzing mixed-effects models in S, S-PLUS and R, developed by the authors, provides the underlying software for implementing the methods presented in the text, being described and illustrated in detail throughout the book.

The balanced mix of real data examples, modeling software, and theory makes this book a useful reference for practitioners who use, or intend to use, mixed-effects models in their data analyses. It can also be used as a text for a one-semester graduate-level applied course in mixed-effects models. Researchers in statistical computing will also find this book appealing for its presentation of novel and efficient computational methods for fitting linear and nonlinear mixed-effects models.

José C. Pinheiro has been a member of the technical staff in statistics research at Bell Laboratories since 1996. He received his Ph.D. in Statistics from the University of Wisconsin-Madison in 1994 and worked for two years in the Department of Biostatistics at the UW--Madison. The author of several articles in mixed-effects models, he is a member of the American Statistical Association and the Biometric Society. Douglas M. Bates is Professor of Statistics at the University of Wisconsin--Madison. The author, with Donald G. Watts, of ``Nonlinear Regression Analysis and Its Applications'', he is a Fellow of the American Statistical Association and a former chair of its Statistical Computing Section.


  1. Linear Mixed-Effects Models
  2. Theory and Computational Methods for LME Models
  3. Describing the Structure of Grouped Data
  4. Fitting Linear Mixed-Effects Models
  5. Extending the Basic Linear Mixed-Effects Model
  6. NLME Models: Basic Concepts and Motivating Examples
  7. Theory and Computational Methods for NLME Models
  8. Fitting Nonlinear Mixed-Effects Models


  1. Data Used in Examples and Exercises
  2. S Functions and Classes
  3. A Collection of Self-Starting Nonlinear Regression Models

Scripts and Complements

Scripts for the examples in the book are available as MEMSS.tar.gz (a gzipped tar file) and MEMSS.zip (a zip file in the INFO-ZIP projects' format). Unpack these by one of

      gzip -dc MEMSS.tar.gz | tar xvf -
      tar zxvf MEMSS.tar.gz                     (GNU tar only)
      unzip MEMSS.zip
which will unzip the material into one directory for each chapter.


An errata list.


Dr José C. Pinheiro
Bell Labs
Lucent Technologies
700 Mountain Ave
Murray Hill, NJ 07974-0636

Email: jcp@bell-labs.com

Professor D. M. Bates
Department of Statistics
1210 W Dayton St
Madison, WI 53706-1685

Email: bates@stat.wisc.edu


Links are provided to Springer's home pages in Germany and the USA, and the preview page for this book.

Last edited on Monday May 8 2000 by Douglas Bates bates@stat.wisc.edu