Controlled clinical trials
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Response-adaptive designs in clinical trials are schemes for patient assignment to treatment, the goal of which is to place more patients on the better treatment based on patient responses already accrued in the trial. While ethically attractive at first glance, these designs have had very little use in practice; yet the statistical literature is rich on this subject. ⋯ We also discuss reasons for the lack of use of these models, and areas of current and future research to address the weaknesses of these methods. We conclude that these designs may be applicable in some situations and describe conditions under which such a trial may be feasible.
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Control Clin Trials · Feb 1992
ReviewImpact of random assignment on study outcome: an empirical examination.
Sixty research investigations published in the biomedical literature were analyzed to examine the effect of design attributes on outcome. All 60 studies included a controlled trial involving a pretest, a therapeutic intervention, and a posttest across at least two groups. Thirty of the trials used random assignment of participants to treatment or control conditions and 30 trials employed some nonrandom method of subject assignment. ⋯ Data analysis revealed that the trial results, as measured by effect size, did not vary across therapeutic trials using random assignment versus those using nonrandom allocation of subjects. The impact of design attributes in the interpretation of multiple clinical trials addressing a similar research question is examined. The argument is made that various design attributes frequently associated with methodological quality should be considered as important moderator variables and their influence on trial outcome should not be assumed a priori but rather examined empirically.
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This is the first of five articles on the properties of different randomization procedures used in clinical trials. This paper presents definitions and discussions of the statistical properties of randomization procedures as they relate to both the design of a clinical trial and the statistical analysis of trial results. The subsequent papers consider, respectively, the properties of simple (complete), permuted-block (i.e., blocked), and urn (adaptive biased-coin) randomization. ⋯ In an unmasked study, the potential for selection bias may be substantial with highly predictable sequences. Finally, the Efron model for accidental bias in the estimate of treatment effect in a linear model is described. This is important because the potential for accidental bias is equivalent to the potential for a covariate imbalance.(ABSTRACT TRUNCATED AT 400 WORDS)