Inference for a Class of Transformed Hazards Models

We consider a new class of transformed hazard rate models. This class contains both the multiplicative hazards model and the additive hazards model as special cases. The sieve maximum likelihood estimators are derived for the model parameters and the estimators for the regression coefficients are shown to be consistent and asymptotically normal with variance achieving the semiparametric efficiency bound. Simulation studies are conducted to examine the small-sample properties of the proposed estimates and a real dataset is used to illustrate our approach.