Conditional screening for ultrahigh-dimensional survival data in case-cohort studies.

ABSTRACT: The case-cohort design has been widely used to reduce the cost of covariate measurements in large cohort studies. In many such studies, the number of covariates is very large, and the goal of the research is to identify active covariates which have great influence on response. Since the introduction of sure independence screening, screening procedures have achieved great success in terms of effectively reducing the dimensionality and identifying active covariates. However, commonly used screening methods are based on marginal correlation or its variants, they may fail to identify hidden active variables which are jointly important but are weakly correlated with the response. Moreover, these screening methods are mainly proposed for data under the simple random sampling and can not be direc

SUBMITTER: Zhang J 

PROVIDER: S-EPMC8561435 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature