Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application of generalized linear mixed models and its related models in the statistical design and analysis of repeated measures from randomized controlled trials. The author introduces a new repeated measures design called S:T design combined with mixed models as a practical and useful framework of parallel group RCT design because of easy handling of missing data and sample size reduction. The book emphasizes practical, rather than theoretical, aspects of statistical analyses and the interpretation of results. It includes chapters in which the author describes some old-fashioned analysis designs that have been in the literature and compares the results with those obtained from the corresponding mixed models.
The book will be of interest to biostatisticians, researchers, and graduate students in the medical and health sciences who are involved in clinical trials.
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Data sets and programs used in the book are available at http://www.medstat.jp/downloadrepeatedcrc.html
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"The main focus of this book is to introduce the generalized linear mixed-effects models with S:T repeated measures design, which provide a flexible and powerful tool to deal with longitudinal data with heterogeneity or variability among subject-specific responses and missing data. This book illustrates theoretical methodologies with a focus on the practicality with a wealth of real-life examples making it easy to understand the topics. It is well organized and contains SAS codes and outputs as useful references. In summary, this is an excellent book with a very good selection of examples. It is clearly written and is enjoyable to read."
~Misoo C. Ellison, Merck & Co., Inc., Kenilworth, NJ
Toshiro Tango is the Director of Center for Medical Statistics, Tokyo. His research interests include various aspects of biostatistics including design and analysis of clinical trials and spatial epidemiology. He has served as associate editor for several journals including Biometrics and Statistics in Medicine, and is the author of Statistical Methods for Disease Clustering.
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