Faculty, Staff and Student Publications

Language

English

Publication Date

2-11-2025

Journal

Communications in Statistics

DOI

10.1080/03610926.2025.2458183

PMID

40895373

PMCID

PMC12396585

PubMedCentral® Posted Date

2-11-2026

PubMedCentral® Full Text Version

Author MSS

Abstract

Statistical methods have been developed for regression modeling of the cumulative incidence function (CIF) given left-truncated right-censored competing risks data. Nevertheless, existing methods typically involve complicated weighted estimating equations or nonparametric conditional likelihood function and often require a restrictive assumption that censoring and/or truncation times are independent of failure time. The pseudo-observation (PO) approach has been used in regression modeling of CIF for right-censored competing risks data under covariate-independent censoring or covariate-dependent censoring. We extend this approach to left-truncated right-censored competing risks data and propose to directly model the CIF based on POs, under general truncation and censoring mechanisms. We adjust for covariate-dependent truncation and/or covariate-dependent censoring by incorporating covariate-adjusted weights into the inverse probability weighted (IPW) estimator of the CIF. We derive large sample properties of the proposed estimators under reasonable model assumptions and regularity conditions and assess their finite sample performances by simulation studies under various scenarios. We apply the proposed method to a cohort study on pregnancy exposed to coumarin derivatives.

Keywords

Competing risks, cumulative incidence function, dependent truncation/censoring, inverse probability weighting, pseudo-observations

Published Open-Access

yes

Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.