Fitting additive hazards models for case‐cohort studies: a multiple imputation approach. (20th July 2015)

• Record Type: Journal Article
• Authors: Jung, Jinhyouk; Harel, Ofer; Kang, Sangwook
• Is Part Of: Statistics in medicine. Volume 35:Number 17(2016)
• Page Start: 2975
• Page End: 2990
• Publication Date: 2015-07-20
• Subjects: additive hazards model -- missing by design -- multiple imputation -- rejection sampling -- survival analysis; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.6588
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : In this paper, we consider fitting semiparametric additive hazards models for case‐cohort studies using a multiple imputation approach. In a case‐cohort study, main exposure variables are measured only on some selected subjects, but other covariates are often available for the whole cohort. We consider this as a special case of a missing covariate by design. We propose to employ a popular incomplete data method, multiple imputation, for estimation of the regression parameters in additive hazards models. For imputation models, an imputation modeling procedure based on a rejection sampling is developed. A simple imputation modeling that can naturally be applied to a general missing‐at‐random situation is also considered and compared with the rejection sampling method via extensive simulation studies. In addition, a misspecification aspect in imputation modeling is investigated. The proposed procedures are illustrated using a cancer data example. Copyright © 2015 John Wiley & Sons, Ltd.