A weighted quantile sum regression with penalized weights and two indices.

ABSTRACT:

Background

New statistical methodologies were developed in the last decade to face the challenges of estimating the effects of exposure to multiple chemicals. Weighted Quantile Sum (WQS) regression is a recent statistical method that allows estimating a mixture effect associated with a specific health effect and identifying the components that characterize the mixture effect.

Objectives

In this study, we propose an extension of WQS regression that estimates two mixture effects of chemicals on a health outcome in the same model through the inclusion of two indices, one in the positive direction and one in the negative direction, with the introduction of a penalization term.

Methods

To evaluate the performance of this new model we performed both a simulation study and a

SUBMITTER: Renzetti S 

PROVIDER: S-EPMC10392701 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature