A new semiparametric estimation method for accelerated hazard model
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Updated: Jun 3, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Jiajia Zhang1, Yingwei Peng, Ou Zhao
1Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina 29208, USA. jzhang@mailbox.sc.edu
Abstract:
The accelerated hazard model has been proposed for more than a decade. However, its application is still very limited, partly due to the complexity of the existing semiparametric estimation method. We propose a new semiparametric estimation method based on a kernel-smoothed approximation to the limit of a profile likelihood function of the model. The method leads to smooth estimating equations and is easy to use. The estimates from the method are proved to be consistent and asymptotically normal. Our numerical study shows that the new method is more efficient than the existing method. The proposed method is employed to reanalyze the data from a brain tumor treatment study.
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