Mixed Models: Theory and Applications with R
Eugene Demidenko
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.”
—Journal of the American Statistical Association
Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R.
The new edition provides in-depth ... Read more
Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as:
- Comprehensive theoretical discussions illustrated by examples and figures
- Over 300 exercises, end-of-section problems, updated data sets, and R subroutines
- Problems and extended projects requiring simulations in R intended to reinforce material
- Summaries of major results and general points of discussion at the end of each chapter
- Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations
Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.
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About Eugene Demidenko
Reviews for Mixed Models: Theory and Applications with R