CitationHao, Lingxin; D'Souza, Stephanie; & Wang, Qi (2018). Genes, social environments, and population studies of child outcomes: Innovative multi-sample data synthesis. Annual Meeting of the Population Association of America. Denver, CO.
AbstractDespite the recent growth in studies of genomics and socioeconomic outcomes, research on gene-by-environment interaction is frequently lacking. Combining information from multiple samples would be a viable option. The primary objective of this paper is to perform and evaluate the feasibility and compatibility of combining multiple samples, which do not contain full information. Drawing on econometrics and biostatistics, this paper applies a framework utilizing generalized method of moments (GMM). Specifically, we combine data from two samples drawn from the same population of American children – Add Health and CNLSY – under an idealized situation where we have also located a small, non-representative sample with all covariates. Future work will address non-idealized situation when the small data of all variables are unavailable. Overall, this application, if successful, will open up the opportunity of using multiple samples for interdisciplinary research among social, biomedical, and public health disciplines.
Keyword(s)genetics social environment population studies
Reference TypeConference proceeding
Book TitleAnnual Meeting of the Population Association of America
Series TitleHealth and mortality 3: Population and aging