Partial likelihood estimation of isotonic proportional hazards models.

ABSTRACT: We consider the estimation of the semiparametric proportional hazards model with an unspecified baseline hazard function where the effect of a continuous covariate is assumed to be monotone. Previous work on nonparametric maximum likelihood estimation for isotonic proportional hazard regression with right-censored data is computationally intensive, lacks theoretical justification, and may be prohibitive in large samples. In this paper, partial likelihood estimation is studied. An iterative quadratic programming method is considered, which has performed well with likelihoods for isotonic parametric regression models. However, the iterative quadratic programming method for the partial likelihood cannot be implemented using standard pool-adjacent-violators techniques, increasing the computati

SUBMITTER: Chung Y 

PROVIDER: S-EPMC5969539 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature