Simulation results using GWAS summary statistics are presented in Figure 1, Table 1, and Table S1 in Supplement 2. Simulation results that directly simulated ascertainment variability are presented in Figure S1 in Supplement 1. These results reveal 3 primary findings. First, the field standard approach of using vTotal can produce substantial, downward bias for liability-scale heritability estimates, with bias increasing as a function of the degree of variability in ascertainment across contributing cohorts (Figure 1A; Figure S1 in Supplement 1). Thus, bias was greatest for those conditions when the ascertainment variability was highest across cohorts. Indeed, holding ascertainment variability constant resulted in the same level of bias for different population SNP-based heritability estimates, cohort sample sizes, population prevalence, and levels of unaccounted for population stratification (Table S1 in Supplement 2). For simulations using GWAS summary statistics within a relatively narrow range of conditions and those directly simulating ascertainment variability across a wider range of conditions, the downward bias was as much as approximately 20% and approximately 50%, respectively (Table 1; Figure S1 in Supplement 1). Second, both the field standard
