
doi: 10.1017/jpr.2016.3
AbstractIn clinical trials with two treatment arms, Efron's biased coin design, Efron (1971), sequentially assigns a patient to the underrepresented arm with probabilityp> ½. Under this design the proportion of patients in any arm converges to ½, and the convergence rate isn-1, as opposed ton-½under some other popular designs. The generalization of Efron's design toK≥ 2 arms and an unequal target allocation ratio (q1, . . .,qK) can be found in some papers, most of which determine the allocation probabilitiesps in a heuristic way. Nonetheless, it has been noted that by using inappropriateps, the proportion of patients in theKarms never converges to the target ratio. We develop a general theory to answer the question of what allocation probabilities ensure that the realized proportions under a generalized design still converge to the target ratio (q1, . . .,qK) with raten-1.
clinical trials, More than two treatments, Markov chain, biased coin design, Markov chains (discrete-time Markov processes on discrete state spaces), Applications of statistics to biology and medical sciences; meta analysis, Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), Limit theorems in probability theory, drift conditions, 62P10, unequal allocation, 60F99
clinical trials, More than two treatments, Markov chain, biased coin design, Markov chains (discrete-time Markov processes on discrete state spaces), Applications of statistics to biology and medical sciences; meta analysis, Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), Limit theorems in probability theory, drift conditions, 62P10, unequal allocation, 60F99
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