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Steady‐state statistical properties and implementation of randomization designs with maximum tolerated imbalance restriction for two‐arm equal allocation clinical trials

In recent decades, several randomization designs have been proposed in the literature as better alternatives to the traditional permuted block design (PBD), providing higher allocation randomness under the same restriction of the maximum tolerated imbalance (MTI). However, PBD remains the most frequ...

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Published in:Statistics in medicine 2024-03, Vol.43 (6), p.1194-1212
Main Authors: Zhao, Wenle, Carter, Kerstine, Sverdlov, Oleksandr, Scheffold, Annika, Ryeznik, Yevgen, Cassarly, Christy, Berger, Vance W.
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container_end_page 1212
container_issue 6
container_start_page 1194
container_title Statistics in medicine
container_volume 43
creator Zhao, Wenle
Carter, Kerstine
Sverdlov, Oleksandr
Scheffold, Annika
Ryeznik, Yevgen
Cassarly, Christy
Berger, Vance W.
description In recent decades, several randomization designs have been proposed in the literature as better alternatives to the traditional permuted block design (PBD), providing higher allocation randomness under the same restriction of the maximum tolerated imbalance (MTI). However, PBD remains the most frequently used method for randomizing subjects in clinical trials. This status quo may reflect an inadequate awareness and appreciation of the statistical properties of these randomization designs, and a lack of simple methods for their implementation. This manuscript presents the analytic results of statistical properties for five randomization designs with MTI restriction based on their steady‐state probabilities of the treatment imbalance Markov chain and compares them to those of the PBD. A unified framework for randomization sequence generation and real‐time on‐demand treatment assignment is proposed for the straightforward implementation of randomization algorithms with explicit formulas of conditional allocation probabilities. Topics associated with the evaluation, selection, and implementation of randomization designs are discussed. It is concluded that for two‐arm equal allocation trials, several randomization designs offer stronger protection against selection bias than the PBD does, and their implementation is not necessarily more difficult than the implementation of the PBD.
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subjects Algorithms
allocation randomness
Clinical outcomes
clinical trial
Clinical trials
Markov analysis
maximum tolerated imbalance
Probability
randomization
Statistical analysis
title Steady‐state statistical properties and implementation of randomization designs with maximum tolerated imbalance restriction for two‐arm equal allocation clinical trials
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