统计与数据科学系系列学术报告之四百九十五期

时间：2025年12月15日（星期一）10:00-11:00

主持人：复旦大学管理学院统计与数据科学系蒋斐宇副教授

地点：史带楼302室

报告人：Prof. Fan Li

Duke University

题目：Sample size and power calculations for causal inference in observational studies

摘要：This paper investigates the theoretical foundation and develops analytical formulas for sample size and power calculations for causal inference with observational data. By analysing the variance of the inverse probability weighting estimator of the average treatment effect, we decompose the power calculations into three components: propensity score distribution, potential outcome distribution, and their correlation. We show that to determine the minimal sample size of an observational study, it is sufficient under mild conditions to have two parameters additional to the standard inputs in the power calculation of randomised trials, which quantify the strength of the confounder-treatment and the confounder-outcome association, respectively. For the former, we propose using the Bhattacharyya coefficient, which measures the covariate overlap and, together with the treatment proportion, leads to a uniquely identifiable and easily computable propensity score distribution. For the latter, we propose a sensitivity parameter bounded by the R-squared statistic of the regression of the outcome on covariates. Utilising the Lyapunov Central Limit Theorem on the linear combination of covariates, our procedure does not require distributional assumptions on the multivariate covariates.

We develop an associated R package PSpower.

个人简介：Fan Li is a professor in the Departments of Statistical Science, and Biostatistics and Bioinformatics at Duke University. Her primary research interest is causal inference and health data science. She also works on Bayesian analysis and missing data. She was the editor for Social Science, Biostatistics and Policy of the Annals of Applied Statistics, and an elected fellow of the American Statistical Association and the Institute of Mathematical Statistics (IMS).