A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations

Conclusions: Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study are limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. While GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. This EHP Advance Publication article has been peer-reviewed, revised, and accepted for publication. EHP Advance Publication articles are completely citable using the DOI number assigned to the article. This document will be replaced with the copyedited and formatted version as soon as it is available. Through the DOI number used in the citation, you will be able to access this document at each stage of the publication process. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations. Environ Health Perspect; http://dx.doi.org/10.1289/EHP172 Received: 26 May 2015 Revised: ...
Source: EHP Research - Category: Environmental Health Authors: Tags: Research Article Source Type: research