Journal article
Promoting structural effects of covariates in the cure rate model with penalization
Statistical methods in medical research, Vol.26(5), pp.2078-2092
10/2017
DOI: 10.1177/0962280217708684
PMID: 28480830
Abstract
Cure rate models have been widely adopted for characterizing survival data that have long-term survivors. Under a mixture cure rate model where the population is a mixture of cured and susceptible subjects, a primary goal is to study covariate effects on the cure probability and survival function of the susceptible subjects. In this article, we propose a penalization method for estimating the mixture cure rate model where we explicitly consider the structural effects of covariates. The proposed method is more informative than the standard estimations and more flexible than the existing works on structural effects. Depending on data characteristics, we develop different penalties and corresponding computational algorithms. Simulation shows that the proposed method outperforms the alternatives by more accurately estimating parameters and identifying relevant variables. Two breast cancer datasets, one with low-dimensional clinical variables and the other with high-dimensional genetic variables, are analyzed.
Details
- Title: Subtitle
- Promoting structural effects of covariates in the cure rate model with penalization
- Creators
- Xinyan Fan - Xiamen UniversityMengque Liu - Xiamen UniversityKuangnan Fang - Xiamen UniversityYuan Huang - Yale UniversityShuangge Ma - Yale University
- Contributors
- N Balakrishnan (Editor)
- Resource Type
- Journal article
- Publication Details
- Statistical methods in medical research, Vol.26(5), pp.2078-2092
- Publisher
- SAGE Publications
- DOI
- 10.1177/0962280217708684
- PMID
- 28480830
- ISSN
- 0962-2802
- eISSN
- 1477-0334
- Language
- English
- Date published
- 10/2017
- Academic Unit
- Biostatistics
- Record Identifier
- 9984363613702771
Metrics
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