An extended semiparametric model for short-term and long-term hazard ratios. Issue 11 (24th July 2019)

• Record Type: Journal Article
• Authors: Kuk, Anthony Y. C.
• Is Part Of: Journal of statistical computation and simulation. Volume 89:Issue 11(2019)
• Page Start: 2138
• Page End: 2150
• Publication Date: 2019-07-24
• Subjects: Converging hazards -- crossing hazards -- nonparametric maximum likelihood estimation -- time-varying hazard ratio; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2019.1610885
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: In survival analysis, one way to deal with non-proportional hazards is to model short-term and long-term hazard ratios. The existing model of this nature has no control over how fast the hazard ratio is changing over time. We add a parameter to the existing model to allow the hazard ratio to change over time at different speed. A nonparametric maximum likelihood approach is used to estimate the model parameters. The existing model is a special case of the extended model when the speed parameter is 0, which leads naturally to a way of testing the adequacy of the existing model. Simulation results show that there can be substantial bias in the estimation of the short-term and long-term hazard ratio if the speed parameter is fixed incorrectly at 0 rather than estimated. The extended model is fitted to three real data sets to shed new insights, including the observation that converging hazards does not necessarily imply the odds are proportional.