Pseudo-likelihood for case–cohort studies under length-biased sampling

Abstract

ABSTRACTA case–cohort design was proposed by Prentice (1986) in order to reduce costs. It involves the collection of covariate data from all subjects who experience the event of interest, and from the members of a random subcohort. This case–cohort design has been extensively studied, but is exclusively considered for right-censored data. In this article, we propose case–cohort designs adapted to length-biased data under the proportional hazards assumption. A pseudo-likelihood procedure is described for estimating parameters and the corresponding cumulative hazard function. The large sample properties, such as consistency and weak convergence, for such pseudo-likelihood estimators are presented. We also conduct simulation studies to show that the proposed estimators are appropriate for practical use. A real Oscar Awards data is provided.