Inference for restricted mean survival time as a function of restriction time under length-biased sampling.
The restricted mean survival time (RMST) is often of direct interest in clinical studies involving censored survival outcomes. It describes the area under the survival curve from time zero to a specified time point. When data are subject to length-biased sampling, as is frequently encountered in observational cohort studies, existing methods cannot estimate the RMST for various restriction times through a single model. In this article, we model the RMST as a continuous function of the restriction time under the setting of length-biased sampling. Two approaches based on estimating equations are proposed to estimate the time-varying effects of covariates. Finally, we establish the asymptotic properties for the proposed estimators. Simulation studies are performed to demonstrate the finite sample performance. Two real-data examples are analyzed by our procedures.
Duke Scholars
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Related Subject Headings
- Time Factors
- Survival Analysis
- Statistics & Probability
- Models, Statistical
- Humans
- Computer Simulation
- 4905 Statistics
- 4202 Epidemiology
- 1117 Public Health and Health Services
- 0104 Statistics
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Time Factors
- Survival Analysis
- Statistics & Probability
- Models, Statistical
- Humans
- Computer Simulation
- 4905 Statistics
- 4202 Epidemiology
- 1117 Public Health and Health Services
- 0104 Statistics