Mixed Models : Theory and Applications
A rigorous, self-contained examination of mixed model theory and applicationMixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses:Modeling of complex clustered or longitudinal dataM
1 online resource (732 pages)
9780471726135, 0471726133
1058082116
Mixed Models Theory and Applications; Contents; Preface; 1 Introduction: Why Mixed Models?; 2 Mle for Lme Model; 3 Statistical Properties of the Lme Model; 4 Growth Curve Model and Generalizations; 5 Meta-analysis Model; 6 Nonlinear Marginal Model; 7 Generalized Linear Mixed Models; 8 Nonlinear Mixed Effects Model; 9 Diagnostics and Influence Analysis; 10 Tumor Regrowth Curves; 11 Statistical Analysis of Shape; 12 Statistical Image Analysis; 13 Appendix: Useful Facts and Formulas; References; Index
English