NLME: Software for mixed-effects models

Last modified: Wednesday, 03-Oct-01

Mixed-effects models provide a powerful and flexible tool for the analysis of balanced and unbalanced grouped data. These data arise in several areas of investigation and are characterized by the presence of correlation between observations within the same group. Some examples are repeated measures data, longitudinal studies, and nested designs. Classical modeling techniques which assume independence of the observations are not appropriate for grouped data.

The NLME software comprises a set of S (S-PLUS) functions, methods, and classes for the analysis of both linear and nonlinear mixed-effects models. It extends the linear and nonlinear modeling facilities available in release 3 of S and S-PLUS. Written by José C. Pinheiro and Douglas M. Bates , the NLME software is available for Unix and Windows platforms.

Version 3.3.1 of NLME.!! NEW !!

The NLME library has been completely redesigned to emphasize a modular, object-oriented design that facilitates users' incorporating new methods for existing generic functions (e.g. new classes of correlation structures and variance functions). The latest release includes several bug corrections with respect to Release 3.3; no new features have been added.

Getting NLME 3.3.1

Some features of NLME 3.3.1


Mixed-Effects Models in S and S-PLUS !! NEW !! A book published by Springer-Verlag describes the use of NLME in detail and includes many examples of real-life applications involving linear and nonlinear mixed-effects models.

The distribution of NLME 3.3.1 available at this site includes a (relatively incomplete) User's Guide in PDF format. Also included with this distribution is a PDF file with all help files available in NLME 3.3.1. On-line help is available for all functions and fitted objects in the NLME 3.3.1 library.

Documentation on NLME 2.1 is included in chapter 2 (pp. 19-79) of S-PLUS Version 3.4 for Unix Supplement , Data Analysis Products Division, MathSoft, Seattle. The complements to W. Venables and B. Ripley's Modern Applied Statistics with S-PLUS books include new sections on the NLME modeling facilities.

A general reference on nonlinear mixed effects models is M. Davidian and D. Giltinan, Nonlinear Models for Repeated Measurement Data, Chapman and Hall, 1995.

Additional references

José Pinheiro
Douglas Bates