Semiparametric analysis of a generalized linear model with multiple covariates subject to detection limits.

ABSTRACT: Studies on the health effects of environmental mixtures face the challenge of limit of detection (LOD) in multiple correlated exposure measurements. Conventional approaches to deal with covariates subject to LOD, including complete-case analysis, substitution methods, and parametric modeling of covariate distribution, are feasible but may result in efficiency loss or bias. With a single covariate subject to LOD, a flexible semiparametric accelerated failure time (AFT) model to accommodate censored measurements has been proposed. We generalize this approach by considering a multivariate AFT model for the multiple correlated covariates subject to LOD and a generalized linear model for the outcome. A two-stage procedure based on semiparametric pseudo-likelihood is proposed for estimating the

SUBMITTER: Chen LW 

PROVIDER: S-EPMC9588684 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature