Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly.
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 can also methods yet to be developed.
Randomization and Bias in Historical PerspectiveJ. Rosser Matthews
Proper Randomization Reduces the Chance of Waste Biomedical ResearchArturo Marti-Carvajal
Sympathetic bias: a Neglected Source of Selection BiasWilliam C. Grant
The Alleged Benefits of Unrestricted RandomizationVance W. Berger
Restricted Randomization: Pros and CautionsJonathan Chipman
Evolution of Restricted Randomization with Maximum Tolerated ImbalanceWenle Zhao
Evaluating the EvaluationAdriana C. Burgos, Ross J. Kusmick
Selection Bias in Studies with Unequal AllocationOlga M. Kuznetsova
Unrecognized Dual Threats to Internal Validity Relating to RandomizationVance W. Berger, Adriana C. Burgos, Omolola A. Odejimi
Testing for second-order selection bias effect in randomised control trials using reverse propensity score (RPS)Steffen Mickenautsch, Bo Fu
The Berger-Exner Test to Detect Third Order Selection Bias in the Presence of a True Treatment EffectSteffen Mickenautsch, Bo Fu, Vance W. Berger
Adjusting for and detection of selection bias in randomized controlled clinical trialsLieven N. Kennes
Randomization and the randomization test: Two sides of the same coinPatrick Onghena
Randomization tests or permutation tests? A historical and terminological clarificationPatrick Onghena
Flexible Minimization: Synergistic Solution for Selection BiasDonald R. Taves