Mixed-Effects Models in S and S-PLUS (Statistics and Computing)

About this book

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. The authors present a unified model-building strategy for both models and apply this to the analysis of over 20 real datasets from a wide variety of areas including pharmacokinetics agriculture and manufacturing. Much 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. The NLME library for analyzing mixed-effects models in S and S-PLUS developed by the authors provides the underlying software for implementing the methods presented. This balanced mix of real data examples modeling software and theory makes the 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.