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This third edition contains new chapters on re-estimating sample size when testing for average bioequivalence, fitting a nonlinear dose response function, estimating a dose to take forward from phase two to phase three, establishing proof of concept, and recalculating the sample size using conditional power. It employs the specially created R package Crossover, includes updates regarding period baselines and data analysis from very small trials, reflects the availability of new procedures in SAS, and presents proc mcmc as an alternative to WinBUGS for Bayesian analysis.
Design and Analysis of Cross-Over Trials is concerned with a specific kind of comparative trial known as the cross-over trial, in which subjects receive different sequences of treatments. Such trials are widely used in clinical and medical research, and in other diverse areas such as veterinary science, psychology, sports science, and agriculture.
The first edition of this book was the first to be wholly devoted to the subject. The second edition was revised to mirror growth and development in areas where the design remained in widespread use and new areas where it had grown in importance. This new Third Edition:
Complete with real data and downloadable SAS code, Design and Analysis of Cross-Over Trials, Third Edition provides a practical understanding of the latest methods along with the necessary tools for implementation.
Inhaltsverzeichnis
"Jones and Kenward added several valuable case studies to the third edition of their book. The case studies illustrate elegantly the applications of recent innovations in statistical methodologies to cross-over trials. The new edition is an excellent reference for scientists who want to understand cross-over trials or are interested in learning how statistical advancements in the last decade could be used to expand the versatility of cross-over trials."
-Christy Chuang-Stein, Ph. D. , Vice President, Head of Statistical Research and Consulting Center, Pfizer Inc.
"As in the previous two editions, this edition offers a comprehensive coverage on the design and analysis of cross-over trials. With several major noteworthy updates, it will assist statisticians to conveniently tackle practical issues that arise in a cross-over trial. . . The most substantial update is the addition of seven new chapters (Chapters 8-14) in the form of short case studies. These real-world examples cover a wide range of issues and solutions above and beyond what is commonly encountered in a cross-over trial and significantly broaden the book. . . the third edition of Design and Analysis of Cross-Over Trials remains an outstanding reference for statisticians who work on cross-over trials, whether occasionally or frequently."
-Haiying Chen, Wake Forest School of Medicine, in Journal of the American Statistical Association, Volume 111, 2016
"Jones and Kenward present students, academics, and researchers with the third edition of their text, dedicated to an understanding of a comparative trait known as the cross-over trial, through which patients involved in a study received different sequences of treatments. New for the third edition, the text includes seven new chapters devoted to case studies, coverage of the R package Crossover, updates related to the use of period baselines and the analysis of very small trials, and a variety of other features."
-Ringgold, Inc. Book News, February 2015
Praise for the Second Edition:
"In the second edition, updated from the original published in 1989, the authors have added discussions of new, more comprehensive (downloadable) datasets and some additional topics. . . . Substantially updated with more than 130 new references, the book has been thoroughly modernized to reflect new developments in this area. Among the new material added to the book is a chapter on bioequivalence and a discussion of new methods for longitudinal and categorical data. This book continues to be a recommended choice as a valuable reference for clinical statisticians and those who study medical trials where treatments through cross-over design are a feasible approach. For those who already own the first edition, updating to the second will help keep you current on recent developments in this area."
-Journal of the American Statistics Association
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