SeminarsPseudo-Partial Likelihood for Proportional Hazards Models with Biased-Sampling Data
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We obtain a "pseudo-partial likelihood" for proportional hazards models with biased-sampling data by viewing biased-sampling data as left-truncated data. The log pseudo-partial likelihood of the biased-sampling data is the expectation of the log partial likelihood of the left-truncated data conditioned on the observed data. In addition, asymptotic properties of the estimator which maximizes the pseudo-partial likelihood are derived. Applications to length-biased data, biased samples with right censoring, stratified samples, and proportional hazards models with missing covariates are also discussed.
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Wei-Yann Tsai
2008-03-21
14:30:00 - 17:00:00
502 , Freshman Classroom Building
We obtain a "pseudo-partial likelihood" for proportional hazards models with biased-sampling data by viewing biased-sampling data as left-truncated data. The log pseudo-partial likelihood of the biased-sampling data is the expectation of the log partial likelihood of the left-truncated data conditioned on the observed data. In addition, asymptotic properties of the estimator which maximizes the pseudo-partial likelihood are derived. Applications to length-biased data, biased samples with right censoring, stratified samples, and proportional hazards models with missing covariates are also discussed.