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 were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although 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.

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. 2016. A systematic comparison of linear regression–based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848–1856; http://dx.doi.org/10.1289/EHP172
*These authors contributed equally to this work.
**These authors contributed equally to this work.
Address correspondence to L. Agier, Institut Albert Bonniot, CRI INSERM/UJF U82, Rond-point de la Chantourne, 38700 La Tronche, France. Telephone: [phone]. E-mail: [e-mail]
We acknowledge the input of HELIX-Exposomics statistical working group, in particular all participants at the meetings where this study was discussed.
This work was supported by the European Community’s Seventh Framework ...

Source: EHP Research - December 1, 2016 Category: Environmental Health Authors: Web Admin Tags: Research Articles December 2016 Source Type: research