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

ABSTRACT: 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), generalized linear models (GLMs) with fixed pair effects (four studies), within-pair difference analyses (three studies), and pai

SUBMITTER: Fasola S 

PROVIDER: S-EPMC8657152 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature