Abstract Number:
2951
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Pin Li (1), Rachel Tucker (2)
Institutions:
(1) Henry Ford Health, Detroit, MI, (2) University of Michigan, Ann Arbor, MI
Co-Author:
First Author:
Presenting Author:
Abstract Text:
Kaplan-Meier curves and logrank tests are widely used to visualize and compare groups in survival analysis. To reduce the confounding effects due to unbalanced covariates, methods such as matching, weighting and stratification have been used. When comparing a target population to a reference population for the average treatment effect on the treated (ATT), we decided to weight the reference population instead of 1:1 matching based on selected covariates to avoid precision lost. We proposed the weighted version of KM curves and log rank test, which is shown to be a consistent estimate. Simulation is used to illustrate the performance in comparison with score test from cox proportional hazard model. The proposed method is also applied to compare an institutional cancer survival to the national benchmark from the Surveillance, Epidemiology, and End Results (SEER) database in Rshiny App.
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Keywords:
Weighted log-rank test|survival outcome|Kaplan-Meier curve|matching| |
Sponsors:
Biometrics Section
Tracks:
Survival Analysis
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