A simulation study for comparing testing statistics in response-adaptive randomization
Xuemin Gu,J. Jack Lee +1 more
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TLDR
The Cook's correction to chi-square test and Williams' correction to log-likelihood-ratio test are generally recommended for hypothesis test in response-adaptive randomization, especially when sample sizes are small.Abstract:
Background
Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically. However, the small sample properties of commonly used test statistics in response-adaptive randomization are not fully studied.read more
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References
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On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
Book
Group Sequential Methods with Applications to Clinical Trials
TL;DR: A short history of sequential and group sequential methods can be found in this paper, where the authors present a road map for the application of two-sided tests for comparing two treatments with normal response of known variance.
Journal ArticleDOI
The Randomized Play-the-Winner Rule in Medical Trials
L. J. Wei,S. Durham +1 more
TL;DR: In this article, a simple randomized treatment assignment rule is proposed and analyzed in a sequential medical trial, and on the average this rule assigns more patients to the better treatment, and it is applicable to the case where patients have delayed responses to treatments.
Journal ArticleDOI
Play the Winner Rule and the Controlled Clinical Trial
TL;DR: Investigation of the conduct of a clinical trial where the “Play the Winner Rule” (PWR) is used to assign patients to the different therapies shows that over a wide range of situations this rule leads to near optimum results when used in a two-stage manner.
Teacher's Corner Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures
Alan Agresti,Brian Caffo +1 more
TL;DR: In this article, simple adjustments of these confidence intervals based on adding four pseudo observations, half of each type, perform surprisingly well even for small samples, and one can bypass awkward sample size guidelines and use the same formulas with small and large samples.