Accelerated failure time models for semi-competing risks data in the presence of complex censoring.

ABSTRACT: Statistical analyses that investigate risk factors for Alzheimer's disease (AD) are often subject to a number of challenges. Some of these challenges arise due to practical considerations regarding data collection such that the observation of AD events is subject to complex censoring including left-truncation and either interval or right-censoring. Additional challenges arise due to the fact that study participants under investigation are often subject to competing forces, most notably death, that may not be independent of AD. Towards resolving the latter, researchers may choose to embed the study of AD within the "semi-competing risks" framework for which the recent statistical literature has seen a number of advances including for the so-called illness-death model. To the best of our kno

SUBMITTER: Lee KH 

PROVIDER: S-EPMC8140291 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature