Main description:

This is a second edition to the original published by Springer in 2006. The comprehensive volume takes a textbook approach systematically developing the field by starting from linear models and then moving up to generalized linear and non-linear mixed effects models. Since the first edition was published the field has grown considerably in terms of maturity and technicality. The second edition of the book therefore considerably expands with the addition of three new chapters relating to Bayesian models, Generalized linear and nonlinear mixed effects models, and Principles of simulation. In addition, many of the other chapters have been expanded and updated.

Contents:

The Art of Modeling.- Linear Models and Regression.- Nonlinear Models and Regression.- Variance Models, Weighting, and Transformations.- Case Studies in Linear and Nonlinear Modeling.- Linear Mixed Effects Models.- Nonlinear Mixed Effects Models: Theory.- Nonlinear Mixed Effects Models: Practical Issues.- Nonlinear Mixed Effects Models: Case Studies.- Bayesian Modeling.- Generalized Linear Models and Its Extensions.- Principles of Simulation.- Appendix.- Index