Multiple Analyses in Clinical Trials

Multiple analyses in clinical trials involves numerous statistical hypotheses within a single experiment. This book provides a nonmathematical introduction to the commmon issues in these types of trials. The audience is medical students, clinical investigators, pharmaceutical researchers, biostatisticians, and epidemiologists.

From the reviews:

"Moyé's background as a statistician and MD makes him especially qualified to write this bookThe clinical trial examples are a major strength of the bookHis medical background and extensive clinical trials experience shine through." Statistics in Medicine, 2004, 23:3551-3559

"The many examples from well known clinical trials are clearly one of the strengths of this book. It is also fascinating to share the author's experience with the FDA where he attended many meetings of Advisory Committees."Biometrics, December 2005

"According to the preface, this book is written for clinical investigators and research groups within the pharmaceutical industry, medical students and regulators. I admire the eloquency of the author. The author does a remarkable job . Without any doubt, the book is a valuable source of ideas for the intended audience. For statisticians it is an interesting source of experimental setups, that are actually used in practice and that consequently are worth while to be studied." (dr H. W. M. Hendriks, Kwantitatieve Methoden, Issue 72B41, 2005)

"The book is entertaining and informative, sufficiently informal to recruit and retain the intended non-statistical readership, but sufficiently formal to detail methods. The author effectively sets up each issue with examples and conceptual discussion, grounding all in realistic examples." (T. A. Louis, Short Book Reviews, Vol. 24 (2), 2004)

"Here in this book is a special situation for clinical trials in which the investigator must do statistical analyses for a number of different response measurements. The author felt that the clinical investigators needed a book that they could understand. This book is his effort to reach that audience. I like the book's organization. I enjoyed leafing through this book and would certainly enjoy having the opportunity to sit down and read it." (Eric R. Ziegel,Technometrics, Vol. 46 (3), August, 2004)

"This book is written primarily for clinical researchers who are interested in designing and analysing clinical trials. It concentrates on elucidating problems arising from multiple analyses in clinical trials . In general, the book is well written and easy to follow. Although this book is written for clinical investigators, I find it a useful reference book for statisticians in the pharmaceutical industry . Furthermore, senior statisticians may find the non-technical discussions and practical examples useful." (Shuying Yang, Pharmaceutical Statistics, Issue 3, 2004)

Auteur
Multiple analyses in clinical trials involves numerous statistical
hypotheses within a single experiment. This book provides a
nonmathematical introduction to the commmon issues in these types of
trials. The audience is medical students, clinical investigators,
pharmaceutical researchers, biostatisticians, and epidemiologists.

Texte du rabat

Concentrating on the rationale for the analyses, the difficulties posed by their interpretation, easily understood solutions, and useful problem sets, this book will help clinical investigators understand multiple analysis procedures and key issues. It is written for advanced medical students, clinical investigators at all levels, research groups within the pharmaceutical industry, regulators at the local, state, and federal level, and biostatisticians.

Contenu
Prologue.- Fundamentals of Clinical Trial Design.- Multiple Analyses and the Random Experiment.- The Lure and Complexity of Multiple Analyses.- Multiple Analyses and Multiple Endpoints.- to Multiple Dependent Analyses I.- Multiple Dependent Analyses II.- to Composite Endpoints.- Multiple Analyses and Composite Endpoints.- to Subgroup Analyses.- Subgroups II: Effect Domination and Controversy.- Subgroups III: Confirmatory Analyses.- Multiple Analyses and Multiple Treatment Arms.- Combining Multiple Analyses.- Conclusions: The Two-Front War.