Nan, Bin; Yu, Menggang; Kalbfleisch, John D. Censored linear regression for case-cohort studies. (English) Zbl 1436.62460 Biometrika 93, No. 4, 747-762 (2006). Summary: Right-censored data from a classical case-cohort design and a stratified case-cohort design are considered. In the classical case-cohort design the subcohort is obtained as a simple random sample of the entire cohort, whereas in the stratified design this subcohort is elected by independent Bernoulli sampling with arbitrary selection probabilities. For each design and under a linear regression model, methods for estimating the regression parameters are proposed and analysed. These methods are derived by modifying the linear ranks tests and estimating equations that arise from full-cohort data using methods that are similar to the pseudolikelihood estimating equation that has been used in relative risk regression for these models. The estimators so obtained are shown to be consistent and asymptotically normal. Variance estimation and numerical illustrations are also provided. Cited in 16 Documents MSC: 62N01 Censored data models 62J05 Linear regression; mixed models 62F10 Point estimation 62F12 Asymptotic properties of parametric estimators 62P10 Applications of statistics to biology and medical sciences; meta analysis Keywords:case-cohort design; censored linear regression; counting process; martingale; rank statistic PDF BibTeX XML Cite \textit{B. Nan} et al., Biometrika 93, No. 4, 747--762 (2006; Zbl 1436.62460) Full Text: DOI