Proportional cause-specific reversed hazards model

Abstract

The proportional reversed hazards model explains the multiplicative effect of covariates on the baseline reversed hazard rate function of lifetimes. In the present study, we introduce a proportional cause-specific reversed hazards model. The proposed regression model facilitates the analysis of failure time data with multiple causes of failure under left censoring. We estimate the regression parameters using a partial likelihood approach. We provide Breslow's type estimators for the cumulative cause-specific reversed hazard rate functions. Asymptotic properties of the estimators are discussed. Simulation studies are conducted to assess their performance. We illustrate the applicability of the proposed model using a real data set.

Keywords:

• cause-specific reversed hazard rate functions
• proportional reversed hazards model
• left censoring
• competing risks

Acknowledgements

We thank the editor and reviewers for their valuable comments and suggestions. The second author would like to thank Department of Science and Technology, Government of India for providing financial support for this work under INSPIRE fellowship.

Disclosure statement

No potential conflict of interest was reported by the authors.