TESTING LIMITED OVERLAP
提出一个统计检验方法，用于评估观察性研究中处理组和对照组特征差异导致的有限重叠程度，拒绝原假设表明重叠问题不严重，标准处理效应估计量表现良好。
Extreme propensity scores arise in observational studies when treated and control units have very different characteristics. This is commonly referred to as limited overlap . In this paper, we propose a formal statistical test that helps assess the degree of limited overlap. Rejecting the null hypothesis in our test indicates either no or very mild degree of limited overlap and hence reassures that standard treatment effect estimators will be well behaved. One distinguishing feature of our test is that it only requires the use of a few extreme propensity scores, which is in stark contrast to other methods that require consistent estimates of some tail index. Without the need to extrapolate using observations far away from the tail, our procedure is expected to exhibit excellent size properties, a result that is also borne out in our simulation study.