Abstract
This paper considers semiparametric estimation of the Cox proportional hazards model for right-censored and length-biased data arising from prevalent sampling. To exploit the special structure of length-biased sampling, we propose a maximum pseudo-profile likelihood estimator, which can handle time-dependent covariates and is consistent under covariate-dependent censoring. Simulation studies show that the proposed estimator is more efficient than its competitors. A data analysis illustrates the methods and theory.
Original language | English (US) |
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Pages (from-to) | 199-210 |
Number of pages | 12 |
Journal | Biometrika |
Volume | 99 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2012 |
Externally published | Yes |
Keywords
- Approximate likelihood
- Cross-sectional sampling
- Product-limit estimator
- Random truncation
- Screening trials
ASJC Scopus subject areas
- Statistics and Probability
- General Mathematics
- Agricultural and Biological Sciences (miscellaneous)
- General Agricultural and Biological Sciences
- Statistics, Probability and Uncertainty
- Applied Mathematics