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Event Detail Information

Event Detail Information

Statistics Seminar - Semiparametric Additive Hazards Regression Models for Case-Cohort/Two-Phase Sampling Designs

Speaker Dr. Yanqing Sun (University of North Carolina at Charlotte)
Date Apr 3, 2014
Time 4:00 pm - 5:15 pm  
Location 165 Everitt
Sponsor Annie Qu
Event type Seminar
Views 921
Under the case-cohort design introduced by Prentice (1986), the covariate histories are ascertained only for the subjects who experience the event of interest (i.e., the cases) during the follow-up period and for a relatively small random sample from the original cohort (i.e., the subcohort). The case-cohort design has been widely used in clinical and epidemiological studies to assess the effects of covariates on failure times. Most statistical methods developed for the case-cohort design use the proportional hazards model, and few methods allow for time-varying regression coefficients. In addition, most methods disregard data from subjects outside of the subcohort, which can result in inefficient inference. Addressing these issues, this paper proposes an estimation procedure for the semiparametric additive hazards model with case-cohort/two-phase sampling data, which allows the effects of some covariates to be time varying while specifying the effects of others to be constant. An augmented inverse probability weighted estimation procedure is proposed, which is more efficient than the widely adopted inverse probability weighted complete-case estimation method. The asymptotic properties of the proposed estimators are established, and the finite-sample properties are examined through an extensive simulation study. The method is applied to analyze data from a preventive HIV vaccine efficacy trial. This is a joint work with Xiyuan Qian, Qiong Shou, and Peter Gilbert.
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