Handling Covariates in the Design of Clinical Trials.
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TLDR
A new class of procedures, covariate-adjusted response adaptive (CARA) randomization procedures that attempt to optimize both efficiency and ethical considerations, while maintaining randomization are advocated.Abstract:
There has been a split in the statistics community about the need for taking covariates into account in the design phase of a clinical trial. There are many advocates of using stratification and covariate-adaptive randomization to promote balance on certain known covariates. However, balance does not always promote efficiency or ensure more patients are assigned to the better treatment. We describe these procedures, including model-based procedures, for incorporating covariates into the design of clinical trials, and give examples where balance, efficiency and ethical considerations may be in conflict. We advocate a new class of procedures, covariate-adjusted response-adaptive (CARA) randomization procedures that attempt to optimize both efficiency and ethical considerations, while maintaining randomization. We review all these procedures, present a few new simulation studies, and conclude with our philosophy.read more
Citations
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Journal ArticleDOI
Rerandomization to improve covariate balance in experiments
Kari Lock Morgan,Donald B. Rubin +1 more
TL;DR: In this article, the authors show that covariate data are available before units are exposed to treatments and can be used to check covariate balance before the physical experiment takes place, provided a precise definition of imbalance has been specified.
Journal ArticleDOI
Adaptive trial designs: a review of barriers and opportunities
TL;DR: This work focuses on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications, and describes a number of current barriers and suggestions for overcoming them in order to promote wider use of appropriate adaptive designs.
Journal ArticleDOI
Rerandomization to improve covariate balance in experiments
Kari Lock Morgan,Donald B. Rubin +1 more
TL;DR: In this paper, the authors show that if covariate data are available before units are exposed to treatments, these chance imbalances can be mitigated by first checking covariate balance before the physical experiment takes place.
Journal ArticleDOI
Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.
TL;DR: Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.
Journal ArticleDOI
Allocation techniques for balance at baseline in cluster randomized trials: a methodological review
Noah Ivers,Ilana Halperin,Jan Barnsley,Jeremy M. Grimshaw,Baiju R. Shah,Baiju R. Shah,Karen Tu,Karen Tu,Ross E.G. Upshur,Merrick Zwarenstein +9 more
TL;DR: The advantages and limitations of different allocation techniques, including stratification, matching, minimization, and covariate-constrained randomization are reviewed as they pertain to C-RCTs to provide investigators with guidance for choosing the best allocation technique for their trial.
References
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Journal ArticleDOI
Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial.
TL;DR: A new general procedure for treatment assignment is described which concentrates on minimizing imbalance in the distributions of treatment numbers within the levels of each individual prognostic factor.
Journal ArticleDOI
The Equivalence of Two Extremum Problems
J. Kiefer,J. Wolfowitz +1 more
TL;DR: In this article, the authors consider the problem of defining probability measures with finite support, i.e., measures that assign probability one to a set consisting of a finite number of points.
Journal ArticleDOI
Forcing a sequential experiment to be balanced
TL;DR: In this paper, a new method of assigning the subjects which tends to balance the experiment, but at the same time is not over vulnerable to various common forms of experimental bias is discussed.
Journal ArticleDOI
Minimization: A new method of assigning patients to treatment and control groups
TL;DR: A new method of assigning patients to treatment and control groups to minimize differences between the groups, not only in the number of patients but in patient characteristics is described, demonstrating a four‐ to fivefold reduction of the probability of severe imbalance, relative to randomization.
Journal ArticleDOI
The method of minimization for allocation to clinical trials: a review
TL;DR: From the evidence presented in this review, it is believed that minimization to be a highly effective allocation method and recommend its wider adoption in the conduct of randomized controlled trials.