Partial-linear single-index Cox regression models with multiple time-dependent covariates.

ABSTRACT:

Background

In cohort studies with time-to-event outcomes, covariates of interest often have values that change over time. The classical Cox regression model can handle time-dependent covariates but assumes linear effects on the log hazard function, which can be limiting in practice. Furthermore, when multiple correlated covariates are studied, it is of great interest to model their joint effects by allowing a flexible functional form and to delineate their relative contributions to survival risk.

Methods

Motivated by the World Trade Center (WTC)-exposed Fire Department of New York cohort study, we proposed a partial-linear single-index Cox (PLSI-Cox) model to investigate the effects of repeatedly measured metabolic syndrome indicators on the risk of developing WTC lung injur

SUBMITTER: Lee M 

PROVIDER: S-EPMC11661057 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature