Semiparametric inference for the proportional odds model with time-dependent covariates

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.