Randomization, Masking, and Allocation Concealment
рдпреЛ рдЗ-рдкреБрд╕реНрддрдХрдХрд╛ рдмрд╛рд░реЗрдорд╛
Far too often the subtle nuances that distinguish proper randomization from flawed randomization are completely ignored in trial reports that state only that randomization was used, with no additional information. Experience has shown that in many cases, the type of randomization that was used was flawed. It is only a matter of time before medical journals and regulatory agencies come to realize that we can no longer rely on (or publish) flawed trials, and that flawed randomization in and of itself disqualifies a trial from being robust or high quality, even if that trial is of high quality otherwise.
This book will help to clarify the role randomization plays in ensuring internal validity, and in drawing valid inferences from the data. The various chapters cover a variety of randomization methods, and are not limited to the most common (and most flawed) ones. Readers will come away with a profound understanding of what constitutes a valid randomization procedure, so that they can distinguish the valid from the flawed among not only existing methods but also methods yet to be developed.
рд▓реЗрдЦрдХрдХреЛ рдмрд╛рд░реЗрдорд╛
Vance W. Berger received holds a doctoral degree in Statistics from Rutgers University. His professional career has included work in the pharmaceutical industry (Janssen Research Foundation, Theradex, and some consulting for Pfizer), work in two centers of the Food and Drug Administration (Drugs and Biologics), and review work for a number of statistical and medical journals. An active researcher, Dr. Berger wrote a book on the design and analysis of randomized clinical trials (focusing on randomization methods). He has also authored numerous book chapters and scientific articles appearing in the peer-reviewed literature, and has presented numerous invited lectures on this topic. Dr. Berger was the recipient of the 2006 Gertrude Cox Award, recognizing "a statistician making significant contributions to statistical practice" by the Washington Statistical Society.
