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πŸ“

Mixed models : theory and applications with R

✍ Scribed by Eugene Demidenko


Publisher
John Wiley & Sons
Tongue
English
Leaves
756
Series
Wiley series in probability and statistics, 893
Category
Library

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No coin nor oath required. For personal study only.

✦ Synopsis


"Mixed 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. The new edition includes Read more...

✦ Table of Contents



Content: Preface --
Preface to the Second Edition --
R software and functions --
Data Sets --
Open Problems in Mixed Models --
1. Introduction: Why Mixed Models? --
2. MLE for the 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.
Abstract:

Praise for the First Edition "This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one's personal library. Read more...

✦ Subjects


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