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

Lydiane Agier | Zendy; Lützen Portengen | Zendy; Marc ChadeauHyam | Zendy; Xavier Basagaña | Zendy; Lise Giorgis-Allemand | Zendy; Valérie Siroux | Zendy; Oliver Robinson | Zendy; Jelle Vlaanderen | Zendy; Juan R. González | Zendy; Mark Nieuwenhuijsen | Zendy; Paolo Vineis | Zendy; Martine Vrijheid | Zendy; Rémy Slama | Zendy; Roel Vermeulen | Zendy

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

Author(s) -

Lydiane Agier,

Lützen Portengen,

Marc ChadeauHyam,

Xavier Basagaña,

Lise Giorgis-Allemand,

Valérie Siroux,

Oliver Robinson,

Jelle Vlaanderen,

Juan R. González,

Mark Nieuwenhuijsen,

Paolo Vineis,

Martine Vrijheid,

Rémy Slama,

Roel Vermeulen

Publication year - 2016

Publication title -

environmental health perspectives

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.257

H-Index - 282

eISSN - 1552-9924

pISSN - 0091-6765

DOI - 10.1289/ehp172

Subject(s) - exposome , linear regression , environmental health , medicine , statistics , biology , mathematics

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures.

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