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Qu, Lianqiang; Wang, Xiaoyu; Sun, Liuquan

Variable screening for varying coefficient models with ultrahigh-dimensional survival data. (English) Zbl 1543.62562

Comput. Stat. Data Anal. 172, Article ID 107498, 12 p. (2022).
Summary: In this article, we develop a variable screening method for varying coefficient hazards models of single-index form. The proposed method can be viewed as a natural survival extension of conditional correlation screening. An appealing feature of the proposed method is that it is applicable to many popularly used survival models, including the varying coefficient additive hazards model and the varying coefficient Cox model. The proposed method enjoys the sure screening property, and the number of the selected covariates can be bounded by a moderate order. Simulation studies demonstrate that our method performs well, and an empirical example is also presented.

Cited in 1 Document

MSC:

62N02 Estimation in survival analysis and censored data
62N01 Censored data models
62P10 Applications of statistics to biology and medical sciences; meta analysis

Keywords:

kernel smoothing; survival data; ultrahigh dimensionality; variable screening; varying coefficient

Software:

uniCox
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Full Text: DOI

References:

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