Causal effect estimation on restricted mean survival time under case-cohort design via propensity score stratification

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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Publication Details

Journal
Lifetime Data Analysis
Published
2025-08-18
DOI
https://doi.org/10.1007/s10985-025-09667-w
Citations
1
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
2.63

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article

Causal effect estimation on restricted mean survival time under case-cohort design via propensity score stratification

Wei-En Lu, Ai Ni
1 citations
Lifetime Data Analysis
Advanced Causal Inference Techniques
2.63
article

Causal effect estimation on restricted mean survival time under case-cohort design via propensity score stratification

Wei-En Lu, Ai Ni
article en
1 citations

Abstract

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.

Lifetime Data AnalysisVol. 31(4)
The Ohio State University (US)
National Heart, Lung, and Blood Institute
Good health and well-being
Openalex Percentile: Top 9%
Advanced Causal Inference Techniques
2.63
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Causal effect estimation on restricted mean survival time under case-cohort design via propensity score stratification — Wei-En Lu, Ai Ni · Lifetime Data Analysis (2025) | TGRS Research Map | TGRS