Semiparametric transformation models of survival-out-of-hospital

Recurrent event data with a terminal event commonly arise in biomedical studies, and the survival-out-of-hospital process is a useful alternative framework for the analysis of recurrent/terminal event data with non-negligible event duration. In this article, we propose a class of semiparametric transformation models for the survival-out-of-hospital process, and the proposed models offer great flexibility in formulating covariate effects on the probability of survival-out-of-hospital. Estimating equation approaches are developed for the model parameters, and the asymptotic properties of the resulting estimators are established. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a Centers for Medicare and Medicaid Services study is provided.