| Literature DB >> 29286533 |
Yinghao Pan1, Jianwen Cai1, Sangmi Kim2, Haibo Zhou1.
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.Entities:
Keywords: Case-cohort design; Estimated likelihood; Secondary outcome; Semiparametric; Validation sample
Mesh:
Year: 2017 PMID: 29286533 PMCID: PMC6026088 DOI: 10.1111/biom.12838
Source DB: PubMed Journal: Biometrics ISSN: 0006-341X Impact factor: 2.571