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Variable selection in semiparametric linear regression with censored data

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  • Brent A. Johnson

Abstract

Summary. We describe two procedures for selecting variables in the semiparametric linear regression model for censored data. One procedure penalizes a vector of estimating equations and simultaneously estimates regression coefficients and selects submodels. A second procedure controls systematically the proportion of unimportant variables through forward selection and the addition of pseudorandom variables. We explore both rank‐based statistics and Buckley–James statistics in the setting proposed and evaluate the performance of all methods through extensive simulation studies and one real data set.

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  • Brent A. Johnson, 2008. "Variable selection in semiparametric linear regression with censored data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 351-370, April.
    • Handle: RePEc:bla:jorssb:v:70:y:2008:i:2:p:351-370
    DOI: 10.1111/j.1467-9868.2008.00639.x
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    Cited by:

    1. Xingwei Tong & Xin He & Liuquan Sun & Jianguo Sun, 2009. "Variable Selection for Panel Count Data via Non‐Concave Penalized Estimating Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 620-635, December.
    2. Brent Johnson & Limin Peng, 2008. "Rank-based variable selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(3), pages 241-252.
    3. Hu, Jianwei & Chai, Hao, 2013. "Adjusted regularized estimation in the accelerated failure time model with high dimensional covariates," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 96-114.
    4. Dennis D. Boos & Leonard A. Stefanski & Yujun Wu, 2009. "Fast FSR Variable Selection with Applications to Clinical Trials," Biometrics, The International Biometric Society, vol. 65(3), pages 692-700, September.
    5. Zou, Yubo & Zhang, Jiajia & Qin, Guoyou, 2011. "A semiparametric accelerated failure time partial linear model and its application to breast cancer," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1479-1487, March.
    6. Cheng, Chao & Feng, Xingdong & Huang, Jian & Jiao, Yuling & Zhang, Shuang, 2022. "ℓ0-Regularized high-dimensional accelerated failure time model," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).
    7. Brent A. Johnson & Qi Long & Matthias Chung, 2011. "On Path Restoration for Censored Outcomes," Biometrics, The International Biometric Society, vol. 67(4), pages 1379-1388, December.

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