Bi-level variable selection for case-cohort studies with group variables.

ABSTRACT: The case-cohort design is an economical approach to estimate the effect of risk factors on the survival outcome when collecting exposure information or covariates on all patients is expensive in a large cohort study. Variables often have group structure such as categorical variables and highly correlated continuous variables. The existing literature for case-cohort data is limited to identifying non-zero variables at individual level only. In this article, we propose a bi-level variable selection method to select non-zero group and within-group variables for case-cohort data when variables have group structure. The proposed method allows the number of variables to diverge as the sample size increases. The asymptotic properties of the estimator including bi-level variable selection consiste

SUBMITTER: Kim S 

PROVIDER: S-EPMC6748310 | biostudies-literature | 2019 Oct-Nov

REPOSITORIES: biostudies-literature