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Propensity score methods to adjust for confounding in assessing treatment effects: bias and precision

机译:倾向评分方法,可在评估治疗效果时进行混淆调整:偏倚和精确度

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摘要

There is an increasing interest in the use of propensity score (PS) methods for confounding control, with generally three ways of estimating adjusted treatment effects in pharmacoepidemiological studies: 1) stratification on PS, 2) matching on PS and 3) using PS as a covariate. To assess bias and precision of different methods, we conducted simulations in three scenarios: 1) treatment had no effect but the crude estimate showed a protective effect; 2) treatment was protective and the crude estimate was more extreme; and 3) treatment increased the risk but the crude estimate showed protective. Adjusting for confounders in all methods shifted the effect estimates toward the true values. Adjusted odds ratios using the PS stratification and the method using PS as a covariate were biased due to either residual confounding or over-adjustment. Matching on PS produced less biased average estimates than other methods but the precision of effect estimates was lower. --------------------------------------------------------------------------------
机译:人们越来越倾向于使用倾向得分(PS)方法来混淆控制,在药物流行病学研究中通常采用三种方法来估计调整后的治疗效果:1)对PS进行分层,2)对PS进行匹配,以及3)使用PS作为协变量为了评估不同方法的偏差和精度,我们在以下三种情况下进行了模拟:1)处理无效,但粗略估计显示出保护效果; 2)治疗具有保护性,粗略估计更为极端; 3)治疗增加了风险,但粗略估计显示出保护作用。在所有方法中对混杂因素进行调整都会使效果估算值偏向真实值。由于残差混杂或过度调整,使用PS分层和使用PS作为协变量的方法调整后的优势比存在偏差。 PS上的匹配产生的平均偏差估计值比其他方法要少,但效果估计的精度较低。 -------------------------------------------------- ------------------------------

著录项

  • 作者

    Wang Zhiqiang;

  • 作者单位
  • 年度 2009
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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