Researchers interested in the genetic causes and correlates of complex phenotypes like externalizing behaviors face a clear quandary in how to optimally bridge the gap between individual SNPs and behavior given the clearly massive polygenicity (C. Chabris et al., 2015; C. F. Chabris et al., 2013) and the unavoidable measurement error when using diagnostic indicators or single manifest scales as outcomes. We believe that the present approach provides advantages on both sides of the genotype-to-phenotype equation, particularly in samples of moderate size. Capturing the common variance across a range of related behaviors and traits both reduces measurement error, and in the present analysis may more accurately represent the broader externalizing dimension that cuts across many psychological disorders and conditions of interest. Indeed, factor analytic approaches to phenotypic measurement may ultimately increase the power to detect meaningful and reliable genetic associations, as evidenced by analyses of simulated data (van der Sluis et al., 2010) and in recent analyses of depression phenotypes (Laurin, Hottenga, Willemsen, Boomsma, & Lubke, 2015).
