Regression analysis for secondary response variable in a case-cohort study.

TitleRegression analysis for secondary response variable in a case-cohort study.
Publication TypeJournal Article
Year of Publication2018
AuthorsPan, Yinghao, Jianwen Cai, Sangmi Kim, and Haibo Zhou
JournalBiometrics
Volume74
Issue3
Pagination1014-1022
Date Published2018 09
ISSN1541-0420
KeywordsCohort Studies, Computer Simulation, Humans, Likelihood Functions, Regression Analysis, Siblings, Statistics as Topic, Statistics, Nonparametric
Abstract

Case-cohort study design has been widely used for its cost-effectiveness. In any real study, there are always other important outcomes of interest beside the failure time that the original case-cohort study is based on. How to utilize the available case-cohort data to study the relationship of a secondary outcome with the primary exposure obtained through the case-cohort study is not well studied. In this article, we propose a non-parametric estimated likelihood approach for analyzing a secondary outcome in a case-cohort study. The estimation is based on maximizing a semiparametric likelihood function that is built jointly on both time-to-failure outcome and the secondary outcome. The proposed estimator is shown to be consistent, efficient, and asymptotically normal. Finite sample performance is evaluated via simulation studies. Data from the Sister Study is analyzed to illustrate our method.

DOI10.1111/biom.12838
Alternate JournalBiometrics
Original PublicationRegression analysis for secondary response variable in a case-cohort study.
PubMed ID29286533
PubMed Central IDPMC6026088
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
P30 ES010126 / ES / NIEHS NIH HHS / United States
R01 ES021900 / ES / NIEHS NIH HHS / United States