Sensitivity analysis for m-estimates, tests, and confidence intervals in matched observational studies
Sensitivity analysis for m-estimates, tests, and confidence intervals in matched observational studies
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DOI：
10.1111/j.1541-0420.2006.00717.x
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发表时间：
2007-06-01
期刊：
影响因子：
1.9
通讯作者：
Rosenbaum, Paul R.
中科院分区：
文献类型：
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作者：
Rosenbaum, Paul R.
Huber的m-估计使用一个估计方程，其中允许观测值具有受控的影响水平。m-估计族包括最小二乘和最大似然，但典型的应用给予极端观测有限的权重。Maritz提出了方法的确切和近似的排列推理的ni-测试，置信区间，估计，这可以来自随机分配的配对受试者的治疗或控制。相反，在观察性研究中，治疗不是随机分配的，观察到的协变量匹配的受试者可能在未观察到的协变量方面存在差异，因此不同的结局可能不是治疗效果。在观察性研究中，敏感性分析方法被开发用于m检验、m区间和m估计：它显示了由于非随机治疗分配而导致的各种程度的偏倚会改变推断的程度。该方法针对两个匹配对（一名治疗受试者与一名对照匹配）和匹配组（一名治疗受试者与一名或多名对照匹配）开发。该方法使用两项研究来说明：（i）暴露于铬和镍对DNA损伤的配对研究，以及（ii）一项具有一个或两个匹配对照的研究，比较两种药物治疗结核病的副作用。该方法产生的敏感性分析：（i）m-测试与Huber的权重函数和其他强大的权重函数，（ii）的置换t-检验，直接使用的意见，和（iii）各种其他程序，如符号测试，Noether的测试，和置换分布的有效分数测试的位置分布族。简要讨论了具有协方差调整的排列推理。
Huber's m-estimates use an estimating equation in which observations are permitted a controlled level of influence. The family of m-estimates includes least squares and maximum likelihood, but typical applications give extreme observations limited weight. Maritz proposed methods of exact and approximate permutation inference for ni-tests, confidence intervals, and estimators, which can be derived from random assignment of paired subjects to treatment or control. In contrast, in observational studies, where treatments are not randomly assigned, subjects matched for observed covariates may differ in terms of unobserved covariates, so differing outcomes may not be treatment effects. In observational studies, a method of sensitivity analysis is developed for m-tests, m-intervals, and m-estimates: it shows the extent to which inferences would be altered by biases of various magnitudes due to nonrandom treatment assignment. The method is developed for both matched pairs, with one treated subject matched to one control, and for matched sets, with one treated subject matched to one or more controls. The method is illustrated using two studies: (i) a paired study of damage to DNA from exposure to chromium and nickel and (ii) a study with one or two matched controls comparing side effects of two drug regimes to treat tuberculosis. The approach yields sensitivity analyses for: (i) m-tests with Huber's weight function and other robust weight functions, (ii) the permutational t-test which uses the observations directly, and (iii) various other procedures such as the sign test, Noether's test, and the permutation distribution of the efficient score test for a location family of distributions. Permutation inference with covariance adjustment is briefly discussed.