Semiparametric inference for the proportional odds model with time-dependent covariates |
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| Affiliation: | 1. Cardiovascular Research Institute Basel (CRIB), Department of Cardiology, University Hospital Basel, University of Basel, Switzerland;2. Department of Internal Medicine, University Hospital Basel, University of Basel, Switzerland;3. Department of Anaesthesiology and Intensive Care, University Hospital Basel, University of Basel, Switzerland;4. Singulex, Alameda, CA, United States;5. Department of Laboratory Medicine, University Hospital Basel, University of Basel, Switzerland;6. Department of Cardiology, Inselspital, University of Bern, Switzerland |
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| Abstract: | ![]()
This paper studies estimation in the proportional odds model, with time-dependent covariates, based on right-censored data. The estimation procedure is an extension of the Yang and Prentice (J. Amer. Statist. Assoc. 94 (1999) 125) approach to the time-dependent covariate case. The proposed estimators include a class of minimum distance estimators defined through weighted empirical odds function. These estimators are shown to be strongly consistent and asymptotically normal, with variances that can be consistently estimated. It also contains a simulation study making comparison of some of the estimators in the class. |
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