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Large, Sparse Optimal Matching With Refined Covariate Balance in an Observational Study of the Health Outcomes Produced by New Surgeons

新外科医生健康结局观察研究中的精细协变量平衡与大规模稀疏最优匹配

Every newly trained surgeon performs her first unsupervised operation. How do the health outcomes of her patients compare with the patients of experienced surgeons? Using data from 498 hospitals, we compare 1252 pairs comprised of a new surgeon and an experienced surgeon working at the same hospital. We introduce a new form of matching that matches patients of each new surgeon to patients of an otherwise similar experienced surgeon at the same hospital, perfectly balancing…

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Amplification of Sensitivity Analysis in Matched Observational Studies

匹配观察研究中敏感性分析的扩维解释

A sensitivity analysis displays the increase in uncertainty that attends an inference when a key assumption is relaxed. In matched observational studies of treatment effects, a key assumption in some analyses is that subjects matched for observed covariates are comparable, and this assumption is relaxed by positing a relevant covariate that was not observed and not controlled by matching. What properties would such an unobserved covariate need to have to materially alter the…

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Sensitivity Analysis for Equivalence and Difference in an Observational Study of Neonatal Intensive Care Units

新生儿重症监护观察研究中等效与差异检验的敏感性分析

In randomized experiments, it is sometimes important to demonstrate that two treatments do not differ greatly in their effects, or to demonstrate that the treatments have very different effects on one outcome but similar effects on another outcome. These “demonstrations” may take the form of rejecting a null hypothesis of inequivalence in an equivalence test, or rejecting a null hypothesis of equal and inequivalent effects on two outcomes. The procedures often express a…

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