Efficient estimation of Cox model with random change point
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Wiley Open Access
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| Natura: | Artículo Open Access |
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Wiley
2024
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| _version_ | 1867017145472253952 |
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| author | Xuerong Chen Yalu Ping Jianguo Sun |
| author_facet | Xuerong Chen Yalu Ping Jianguo Sun Xuerong Chen Yalu Ping Jianguo Sun |
| collection | Wiley Open Access |
| contents | Efficient estimation of Cox model with random change point Xuerong Chen Yalu Ping Jianguo Sun Statistics in Medicine In clinical studies, the risk of a disease may dramatically change when some biological indexes of the human body exceed some thresholds. Furthermore, the differences in individual characteristics of patients such as physical and psychological experience may lead to subject‐specific thresholds or change points. Although a large literature has been established for regression analysis of failure time data with change points, most of the existing methods assume the same, fixed change point for all study subjects. In this paper, we consider the situation where there exists a subject‐specific change point and two Cox type models are presented. The proposed models also offer a framework for subgroup analysis. For inference, a sieve maximum likelihood estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. An extensive simulation study is conducted to assess the empirical performance of the proposed method and indicates that it works well in practical situations. Finally the proposed approach is applied to a set of breast cancer data. 10.1002/sim.9987 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| doi_str_mv | 10.1002/sim.9987 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_sim_9987 |
| institution | Wiley Open Access |
| license_str_mv | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| publishDate | 2024 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Efficient estimation of Cox model with random change point Xuerong Chen Yalu Ping Jianguo Sun Statistics in Medicine Efficient estimation of Cox model with random change point Xuerong Chen Yalu Ping Jianguo Sun Statistics in Medicine In clinical studies, the risk of a disease may dramatically change when some biological indexes of the human body exceed some thresholds. Furthermore, the differences in individual characteristics of patients such as physical and psychological experience may lead to subject‐specific thresholds or change points. Although a large literature has been established for regression analysis of failure time data with change points, most of the existing methods assume the same, fixed change point for all study subjects. In this paper, we consider the situation where there exists a subject‐specific change point and two Cox type models are presented. The proposed models also offer a framework for subgroup analysis. For inference, a sieve maximum likelihood estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. An extensive simulation study is conducted to assess the empirical performance of the proposed method and indicates that it works well in practical situations. Finally the proposed approach is applied to a set of breast cancer data. 10.1002/sim.9987 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| title | Efficient estimation of Cox model with random change point |
| topic | Statistics in Medicine |
| url | https://onlinelibrary.wiley.com/doi/10.1002/sim.9987 |