Nonparametric screening and feature selection for ultrahigh-dimensional Case II interval-censored failure time data.
Nonparametric screening and feature selection for ultrahigh-dimensional Case II interval-censored failure time data.
复制标题
超高维案例 II 区间删失失效时间数据的非参数筛选和特征选择。
DOI：
10.1002/bimj.201900154
复制
发表时间：
2020-12
期刊：
影响因子：
--
通讯作者：
Robison LL
中科院分区：
文献类型：
--
作者：
Hu Q;Zhu L;Liu Y;Sun J;Srivastava DK;Robison LL
对于超高维数据的分析，第一步通常是进行筛选和特征选择，以有效降低维度，同时高概率地保留所有活跃或相关变量。为此，人们在各种框架下开发了许多方法，但大多数方法只适用于完整数据。在本文中，我们考虑了一种不完整数据的情况，即似乎没有筛选程序的情况 II 间隔删失故障时间数据。基于累积残差的思想，我们开发了一种无模型或非参数方法，并证明该方法具有确定的独立筛选特性。特别是，该方法表明，就活跃变量与相关故障时间的关联性而言，活跃变量往往排在非活跃变量之上。为了证明所提方法的实用性，我们进行了一项模拟研究，结果特别表明，该方法在一般生存模型中效果良好，并且能够捕捉具有交互作用的非线性协变量。此外，该方法还被应用于一项儿童癌症幸存者研究，该研究也是本次调查的动机。
For the analysis of ultrahigh-dimensional data, the first step is often to perform screening and feature selection to effectively reduce the dimensionality while retaining all the active or relevant variables with high probability. For this, many methods have been developed under various frameworks but most of them only apply to complete data. In this paper, we consider an incomplete data situation, case II interval-censored failure time data, for which there seems to be no screening procedure. Basing on the idea of cumulative residual, a model-free or non-parametric method is developed and shown to have the sure independent screening property. In particular, the approach is shown to tend to rank the active variables above the inactive ones in terms of their association with the failure time of interest. A simulation study is conducted to demonstrate the usefulness of the proposed method and, in particular, indicates that it works well with general survival models and is capable of capturing the nonlinear covariates with interactions. Also the approach is applied to a childhood cancer survivor study that motivated this investigation.
登录
查看更多内容
DOI：
10.1080/01621459.2013.850086
发表时间：
2014-01-01
影响因子：
3.7
作者：
Liu J;Li R;Wu R
通讯作者：
Wu R
影响因子：
3.7
作者：
Fan J;Feng Y;Song R
通讯作者：
Song R
影响因子：
4.5
作者：
Chang J;Tang CY;Wu Y
通讯作者：
Wu Y
影响因子：
4.5
作者：
Mai, Qing;Zou, Hui
通讯作者：
Zou, Hui
DOI：
10.1080/01621459.2013.879828
发表时间：
2014-07-03
影响因子：
3.7
作者：
Fan, Jianqing;Ma, Yunbei;Dai, Wei
通讯作者：
Dai, Wei