Sufficient variable screening via directional regression with censored response

Spearman Rank Correlation Screening for Ultrahigh-dimensional Censored Data

Herein, we propose a Spearman rank correlation based screening procedure for ultrahigh-dimensional data with censored response case. The proposed method is model-free without specifying any regression forms of predictors or response variable and is robust under the unknown monotone transformations of these response variable and predictors. The sure-screening and rank-consistency properties are established under some mild regularity conditions. Simulation studies demonstrate that the new screening method performs well in the presence of a heavy-tailed distribution, strongly dependent predictors…

A Multivariate Cure Model for Left- and Right-Censored Data with Application to Colorectal Cancer Screening Patterns

We develop a multivariate cure survival model to estimate lifetime patterns of colorectal cancer screening. Screening data cover long periods of time, with sparse observations for each person. Some events may occur before the study begins or after the study ends, so the data are both left- and right-censored, and some individuals are never screened (the "cured" population). We propose a multivariate parametric cure model that can be used with left- and right-censored data. Our model allows for the estimation of the time to screening as well as the average number of times individuals will be sc…

无需模型的特征筛选：修订的切塔吉埃秩相关性用于超高维截断数据

Model-free Feature Screening via Revised Chatterjee's Rank Correlation for Ultra-high Dimensional Censored Data

本文提出一种基于修订切塔吉埃秩相关性的无需模型特征筛选方法，用于处理超高维截断数据，通过模拟研究和基因表达数据分析展示其有效性。

Iterated Feature Screening based on Distance Correlation for Ultrahigh-Dimensional Censored Data with Covariates Measurement Error

Feature screening is an important method to reduce the dimension and capture informative variables in ultrahigh-dimensional data analysis. Many methods have been developed for feature screening. These methods, however, are challenged by complex features pertinent to the data collection as well as the nature of the data themselves. Typically, incomplete response caused by right-censoring and covariates measurement error are often accompanying with survival analysis. Even though there are many methods have been proposed for censored data, little work has been available when both incomplete respo…

区间删失三状态筛查结局的贝叶斯加速失效时间模型

A Bayesian accelerated failure time model for interval censored three-state screening outcomes

本文针对区间删失且仅在同一筛查区间内才能观测到CIN-2至CIN-3进展的三状态筛查数据，提出贝叶斯加速失效时间模型，并利用截断分布数据扩充的Metropolis-within-Gibbs算法估计HPV到CIN-3及CIN-2到CIN-3的转移时间。

基于受限平均生存时间的高维特征筛选用于非线性关联分析

High-dimensional Feature Screening for Nonlinear Associations With Survival Outcome Using Restricted Mean Survival Time

本文提出一种基于受限平均生存时间差异的无模型特征筛选方法，用于识别超高维生存数据中与响应变量具有非线性、非单调或局部关联的重要特征，并具备确定筛选性质及处理多重共线性的迭代程序。