Observational analysis estimates causal effects on restricted mean survival time in survival outcomes, suggesting improved methods for cost efficiency.
In large observational studies with survival outcome and low event rates, the case-cohort design is commonly used to reduce the cost associated with covariate measurement. The restricted mean survival time (RMST) difference has been increasingly used as an alternative to hazard ratio when estimating the causal effect on survival outcomes. We investigate the estimation of marginal causal effect on RMST under the stratified case-cohort design while adjusting for measured confounders through propensity score stratification. The asymptotic normality of the estimator is established, and its variance formula is derived. Simulation studies are performed to evaluate the finite sample performance of the proposed method compared to several alternative methods. Finally, we apply the proposed method to the Atherosclerosis Risk in Communities study to estimate the marginal causal effect of high-sensitivity C-reactive protein level on coronary heart disease-free survival.
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Lu et al. (2025) studied this question.
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