Flexible semi-parametric regression of state occupational probabilities in a multistate model with right-censored data.

ABSTRACT: Inference for the state occupation probabilities, given a set of baseline covariates, is an important problem in survival analysis and time to event multistate data. We introduce an inverse censoring probability re-weighted semi-parametric single index model based approach to estimate conditional state occupation probabilities of a given individual in a multistate model under right-censoring. Besides obtaining a temporal regression function, we also test the potential time varying effect of a baseline covariate on future state occupation. We show that the proposed technique has desirable finite sample performances and its performance is competitive when compared with three other existing approaches. We illustrate the proposed methodology using two different data sets. First, we re-examine

SUBMITTER: Siriwardhana C 

PROVIDER: S-EPMC5816729 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature