ADAPTIVE ALLOCATION IN RANDOMIZED CONTROLLED TRIALS
ADAPTIVE ALLOCATION IN RANDOMIZED CONTROLLED TRIALS
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DOI：
10.1016/0197-2456(85)90120-5
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发表时间：
1985-01-01
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影响因子：
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通讯作者：
BIRKETT, NJ
中科院分区：
文献类型：
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作者：
BIRKETT, NJ
当预后因素数量较多时，适应性分配被提出作为一种降低随机对照试验中重要预后因素机会失衡风险的程序。在这篇文章中，最小化，一种自适应分配，比较简单的随机化和分层分配的一系列蒙特卡罗模拟。三个结果进行了研究：估计的治疗效果，拒绝区域的大小和功率。与简单随机化相比，最小化产生了治疗效果的无偏估计值，并增加了把握度。对于最小化和分层分配，学生的t检验结果都是保守的。最小化和分层在把握度方面产生了类似的改善，但有证据表明，当某些预后变量无法纳入分层分配方案时，最小化可能产生比分层更高的把握度。
Adaptive allocation has been proposed as a procedure to reduce the risk of chance imbalance of important prognostic factors in randomized controlled trials when the number of prognostic factors is large. In this article, minimization, a type of adaptive allocation, is compared to simple randomization and stratified allocation in a series of Monte Carlo simulations. Three outcomes are studied: estimated treatment effect, size of the rejection region, and power. Minimization produced an unbiased estimate of treatment effect and increased power when compared to simple randomization. Student''s t text was conservative for both minimization and stratified allocation. Minimization and stratification produced similar improvements in power but there was some evidence that minimization might produce higher power than stratification when some prognostic variables cannot be included in the stratified allocation scheme.