Pan, Yinghao; Cai, Jianwen; Kim, Sangmi; Zhou, Haibo Regression analysis for secondary response variable in a case-cohort study. (English) Zbl 1414.62469 Biometrics 74, No. 3, 1014-1022 (2018). Summary: 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. Cited in 1 Document MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 62K20 Response surface designs 62P20 Applications of statistics to economics 62J02 General nonlinear regression Keywords:case-cohort design; estimated likelihood; secondary outcome; semiparametric estimation; validation sample; regression analysis PDFBibTeX XMLCite \textit{Y. Pan} et al., Biometrics 74, No. 3, 1014--1022 (2018; Zbl 1414.62469) Full Text: DOI Link