A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

TitleA regularized variable selection procedure in additive hazards model with stratified case-cohort design.
Publication TypeJournal Article
Year of Publication2018
AuthorsNi, Ai, and Jianwen Cai
JournalLifetime Data Anal
Volume24
Issue3
Pagination443-463
Date Published2018 07
ISSN1572-9249
KeywordsAlgorithms, Atherosclerosis, Biostatistics, Cohort Studies, Epidemiologic Studies, Humans, Proportional Hazards Models, Risk Assessment, Survival Analysis
Abstract

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

DOI10.1007/s10985-017-9402-7
Alternate JournalLifetime Data Anal
Original PublicationA regularized variable selection procedure in additive hazards model with stratified case-cohort design.
PubMed ID28755021
PubMed Central IDPMC5787409
Grant ListN01HC55020 / HL / NHLBI NIH HHS / United States
N01HC55018 / HL / NHLBI NIH HHS / United States
N01HC55022 / HL / NHLBI NIH HHS / United States
N01HC55015 / HL / NHLBI NIH HHS / United States
P30 CA008748 / CA / NCI NIH HHS / United States
N01HC55016 / HL / NHLBI NIH HHS / United States
N01HC55019 / HL / NHLBI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
N01HC55021 / HL / NHLBI NIH HHS / United States
R01 ES021900 / ES / NIEHS NIH HHS / United States