0000000000237797

AUTHOR

Benjamin Cuer

0000-0002-5634-0704

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A Critical Review of Statistical Methods for Twin Studies Relating Exposure to Early Life Health Conditions

2021

International audience; When investigating disease etiology, twin data provide a unique opportunity to control for confounding and disentangling the role of the human genome and exposome. However, using appropriate statistical methods is fundamental for exploiting such potential. We aimed to critically review the statistical approaches used in twin studies relating exposure to early life health conditions. We searched PubMed, Scopus, Web of Science, and Embase (2011–2021). We identified 32 studies and nine classes of methods. Five were conditional approaches (within-pair analyses): additive-common-erratic (ACE) models (11 studies), generalized linear mixed models (GLMMs, five studies), gene…

ExposomeComputer scienceHealth Toxicology and MutagenesisInferenceMarginal modelReviewexposomeGeneralized linear mixed modeltwin data03 medical and health sciences0302 clinical medicineDiscriminative modelchildren[STAT.AP] Statistics [stat]/Applications [stat.AP]StatisticsHumans030212 general & internal medicineGeneralized estimating equationchildren Exposome Genome Health Statistical methods Twin data Humans Linear Models Models Statisticalgenome030304 developmental biology0303 health sciences[STAT.AP]Statistics [stat]/Applications [stat.AP]Models StatisticalConfoundingPublic Health Environmental and Occupational HealthRhealthTwin studychildren exposome genome health statistical methods twin data[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologieLinear Modelsstatistical methodsMedicine[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
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