VARIABLE SELECTION FOR RECURRENT EVENT DATA WITH INFORMATIVE CENSORING

被引:0
|
作者
Ximing CHENG
Li LUO
机构
[1] School of Applied Science,Beijing Information Science and Technology University
[2] Academy of Mathematics and Systems Science,Chinese Academy of Sciences
[3] Information System Management Dept.SINOPEC
关键词
Backward exclusion; estimating equation; forward inclusion; informative censoring; oracle properties; recurrent event data; sparsity;
D O I
暂无
中图分类号
O212.1 [一般数理统计];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Recurrent events data with a terminal event(e.g.,death) often arise in clinical and observational studies.Variable selection is an important issue in all regression analysis.In this paper, the authors first propose the estimation methods to select the significant variables,and then prove the asymptotic behavior of the proposed estimator.Furthermore,the authors discuss the computing algorithm to assess the proposed estimator via the linear function approximation and generalized cross validation method for determination of the tuning parameters.Finally,the finite sample estimation for the asymptotical covariance matrix is also proposed.
引用
收藏
页码:987 / 997
页数:11
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