Propensity Score Weighting for Causal Subgroup Analysis
arXiv:2010.02121
Abstract
A common goal in comparative effectiveness research is to estimate treatment effects on pre-specified subpopulations of patients. Though widely used in medical research, causal inference methods for such subgroup analysis remain underdeveloped, particularly in observational studies. In this article, we develop a suite of analytical methods and visualization tools for causal subgroup analysis. First, we introduce the estimand of subgroup weighted average treatment effect and provide the corresponding propensity score weighting estimator. We show that balancing covariates within a subgroup bounds the bias of the estimator of subgroup causal effects. Second, we design a new diagnostic graph -- the Connect-S plot -- for visualizing the subgroup covariate balance. Finally, we propose to use the overlap weighting method to achieve exact balance within subgroups. We further propose a method that combines overlap weighting and LASSO, to balance the bias-variance tradeoff in subgroup analysis. Extensive simulation studies are presented to compare the proposed method with several existing methods. We apply the proposed methods to the Patient-centered Results for Uterine Fibroids (COMPARE-UF) registry data to evaluate alternative management options for uterine fibroids for relief of symptoms and quality of life.
arXiv comment17 pages, 6 figures
References in corpus (4)
- For objective causal inference, design trumps analysis
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- Varying impacts of letters of recommendation on college admissions: Approximate balancing weights for subgroup effects in observational studies
Cited by in corpus (4)
- PSweight: An R Package for Propensity Score Weighting Analysis
- Varying impacts of letters of recommendation on college admissions: Approximate balancing weights for subgroup effects in observational studies
- Sharp Inference on Selected Subgroups in Observational Studies
- Covariate adjustment in subgroup analyses of randomized clinical trials: A propensity score approach