Estimation of complier causal treatment effects under the case–cohort studies with interval-censored failure time data

Abstract

It has attracted a great deal of interest in randomized survival studies to assess the causal treatment effect under non-compliance with time-to-event outcomes. In this paper, the problem when one faces case–cohort studies for which covariates are usually too expensive to be measured or obtained for the full cohort and also the disease rate is generally low is considered. Furthermore, only interval-censored data may be available for the failure event of interest, a situation for which there does not seem to exist an established estimation procedure. To address the problem, a sieve inverse probability weighting estimation procedure is proposed, and the resulting estimators are shown to be consistent and asymptotically normal. A simulation study is conducted to evaluate the finite sample performance of the proposed approach and suggests that it works well in practice. In addition, the method is applied to a breast cancer screening study.

Keywords:

• Case–cohort study
• complier causal treatment effect
• interval censoring
• proportional hazards model

Acknowledgments

The authors wish to thank the associate editor and a reviewer for their helpful comments and suggestions that greatly improved this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by the Science and Technology Research Planning Project of Jilin Provincial Department of Education (No. JJKH20231144KJ) and the Natural Science Foundation of Jilin Province (No. 20230101002JC).