文章基本信息

标题：Using Propensity Scores for Causal Inference: Pitfalls and Tips
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作者：Koichiro Shiba ; Takuya Kawahara
期刊名称：Journal of Epidemiology
印刷版ISSN：0917-5040
电子版ISSN：1349-9092
出版年度：2021
卷号：31
期号：8
页码：457-463
DOI：10.2188/jea.JE20210145
语种：English
出版社：Japan Epidemiological Association
摘要：Methods based on propensity score (PS) have become increasingly popular as a tool for causal inference. A better understanding of the relative advantages and disadvantages of the alternative analytic approaches can contribute to the optimal choice and use of a specific PS method over other methods. In this article, we provide an accessible overview of causal inference from observational data and two major PS-based methods (matching and inverse probability weighting), focusing on the underlying assumptions and decision-making processes. We then discuss common pitfalls and tips for applying the PS methods to empirical research and compare the conventional multivariable outcome regression and the two alternative PS-based methods (ie, matching and inverse probability weighting) and discuss their similarities and differences. Although we note subtle differences in causal identification assumptions, we highlight that the methods are distinct primarily in terms of the statistical modeling assumptions involved and the target population for which exposure effects are being estimated.
关键词：propensity score;matching;inverse probability weighting;target population