Rank-based variable selection with censored data.
Rank-based variable selection with censored data.
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DOI:
10.1007/s11222-009-9126-y
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发表时间:
2010-04-01
影响因子:
2.2
通讯作者:
Ying Z
中科院分区:
文献类型:
--
作者:
Xu J;Leng C;Ying Z
A rank-based variable selection procedure is developed for the semiparametric accelerated failure time model with censored observations where the penalized likelihood (partial likelihood) method is not directly applicable. The new method penalizes the rank-based Gehan-type loss function with the ℓ1 penalty. To correctly choose the tuning parameters, a novel likelihood-based χ2-type criterion is proposed. Desirable properties of the estimator such as the oracle properties are established through the local quadratic expansion of the Gehan loss function. In particular, our method can be easily implemented by the standard linear programming packages and hence numerically convenient. Extensions to marginal models for multivariate failure time are also considered. The performance of the new procedure is assessed through extensive simulation studies and illustrated with two real examples.
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影响因子:
2.7
作者:
Wang, Hansheng;Li, Runze;Tsai, Chih-Ling
通讯作者:
Tsai, Chih-Ling
影响因子:
2.7
作者:
Jin, ZZ;Ying, ZL;Wei, LJ
通讯作者:
Wei, LJ
DOI:
10.1198/016214508000000184
发表时间:
2008-06-01
影响因子:
3.7
作者:
Johnson, Brent A.;Lin, D. Y.;Zeng, Donglin
通讯作者:
Zeng, Donglin
影响因子:
2.7
作者:
WEI, LJ;YING, Z;LIN, DY
通讯作者:
LIN, DY
影响因子:
1
作者:
Jin, Z;Lin, DY;Ying, Z
通讯作者:
Ying, Z