Paige Harden (University of Texas, Austin)
Genome-wide association studies (GWAS) perform “hypothesis-free” statistical tests of the correlation between millions of genetic variants and a measured phenotype, such as height, body mass index, psychiatric disease, sexual orientation, or educational attainment. The value of GWAS for discovering the causes of human behavior and disease remains hotly debated. In this presentation, I suggest that these debates partly stem from conflict between different models of causation. I consider how GWAS results map to the counterfactual “potential outcomes” framework for causal inference that is frequently employed within the social sciences, in contrast to the emphasis on mechanism in the biological sciences.
