Cox regression model under dependent truncation.

ABSTRACT: Truncation is a statistical phenomenon that occurs in many time-to-event studies. For example, autopsy-confirmed studies of neurodegenerative diseases are subject to an inherent left and right truncation, also known as double truncation. When the goal is to study the effect of risk factors on survival, the standard Cox regression model cannot be used when the survival time is subject to truncation. Existing methods that adjust for both left and right truncation in the Cox regression model require independence between the survival times and truncation times, which may not be a reasonable assumption in practice. We propose an expectation-maximization algorithm to relax the independence assumption in the Cox regression model under left, right, or double truncation to an assumption of conditio

SUBMITTER: Rennert L 

PROVIDER: S-EPMC8426413 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature