Cox regression with dependent error in covariates.

ABSTRACT: Many survival studies have error-contaminated covariates due to the lack of a gold standard of measurement. Furthermore, the error distribution can depend on the true covariates but the structure may be difficult to characterize; heteroscedasticity is a common manifestation. We suggest a novel dependent measurement error model with minimal assumptions on the dependence structure, and propose a new functional modeling method for Cox regression when an instrumental variable is available. This proposal accommodates much more general error contamination than existing approaches including nonparametric correction methods of Huang and Wang (2000, Journal of the American Statistical Association 95, 1209-1219; 2006, Statistica Sinica 16, 861-881). The estimated regression coefficients are consiste

SUBMITTER: Huang Y 

PROVIDER: S-EPMC5756534 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature