Propensity scores used for analysis of cluster randomized trials with selection bias: a simulation study

被引:25
作者
Leyrat, C. [1 ,2 ]
Caille, A. [1 ,2 ,3 ,4 ]
Donner, A. [5 ]
Giraudeau, B. [1 ,2 ,3 ,4 ]
机构
[1] INSERM UMR S 738, Paris, France
[2] INSERM CIC 202, F-37044 Tours 9, France
[3] Univ Tours, PRES Ctr Val de Loire Univ, Tours, France
[4] CHRU Tours, Tours, France
[5] Univ Western Ontario, Dept Epidemiol & Biostat, London, ON, Canada
关键词
cluster randomized trial; Monte-Carlo simulations; selection bias; propensity score; INTRACLASS CORRELATION; PRIMARY-CARE; SAMPLE-SIZE; OSTEOARTHRITIS; ADJUSTMENT; MANAGEMENT; BOOTSTRAP; BALANCE;
D O I
10.1002/sim.5795
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cluster randomized trials (CRTs) are often prone to selection bias despite randomization. Using a simulation study, we investigated the use of propensity score (PS) based methods in estimating treatment effects in CRTs with selection bias when the outcome is quantitative. Of four PS-based methods (adjustment on PS, inverse weighting, stratification, and optimal full matching method), three successfully corrected the bias, as did an approach using classical multivariable regression. However, they showed poorer statistical efficiency than classical methods, with higher standard error for the treatment effect, and typeI error much smaller than the 5% nominal level. Copyright (c) 2013 John Wiley & Sons, Ltd.
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页码:3357 / 3372
页数:16
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