Document Type
Honors Project - Open Access
Abstract
Prevalent cohort studies are widely used for their cost-efficiency and convenience. However, in such studies, only the residual lifetime can be observed. Traditionally, researchers rely on self-reported onset times to infer the underlying survival distribution, which may introduce additional bias that confounds downstream analysis. This study compares two stacking procedures and one mixture model approach that uses only residual lifetime data while leveraging the strengths of different estimators. Our simulation results show that the two stacked estimators outperform the nonparametric maximum likelihood estimator (NPMLE) and the mixture model, allowing robust and accurate estimations for underlying survival distributions.
Recommended Citation
Li, Zhaoheng, "A Comparison of Stacking Methods to Estimate Survival Using Residual Lifetime Data from Prevalent Cohort Studies" (2022). Mathematics, Statistics, and Computer Science Honors Projects. 70.
https://digitalcommons.macalester.edu/mathcs_honors/70
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