@article {4772,
	title = {Fitting additive hazards models for case-cohort studies: a multiple imputation approach.},
	journal = {Statistics in medicine},
	year = {2015},
	month = {2015 Jul 20},
	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 {\textcopyright} 2015 John Wiley \& Sons, Ltd.},
	issn = {1097-0258},
	doi = {10.1002/sim.6588},
	author = {Jung, Jinhyouk and Harel, Ofer and Kang, Sangwook}
}
