We provide two examples of how one might use exploratory methods to guide the specification of more nuanced factor models. In the first example, we submitted the LDSC-derived genetic correlation matrix of the 12 neuroticism items in UKB to exploratory factor analysis (EFA; see Supplementary Results). Based on these initial EFA results, follow-up CFAs (Supplementary Figure 3) were specified using Genomic SEM (standardized loadings > .4 were retained; Supplementary Table 2). The two-factor solution (χ2[53] = 2758.18, AIC = 2808.18, CFI = .940, SRMR = .077) and three-factor solution (χ2[51] = 1879.31, AIC = 1933.31, CFI = .959, SRMR = .057) both provided excellent fit to the data and exceeded the fit of the single, common factor model. Consistent with the superior model fit indices for the two- and three-factor solutions, only 28 and 20 of the 69 QSNP hits from the single common factor model (described in further detail, under the SNP Effects section, below) continued to surpass genome-wide significance for the two- and three-factor models, respectively (Supplementary Figure 4; Supplementary Table 3). In addition, a GWAS of all
