Abstract The objectives of this study were to compare (co)variance parameter estimates among subsets of data that were pooled from herds with high, medium, or low individual herd heritability estimates and to compare individual herd heritability estimates to REML heritability estimates for pooled data sets. A regression model was applied to milk yield, fat yield, protein yield, and somatic cell score (SCS) records from 20,902 herds to generate individual-herd heritability estimates. Herds representing the 5th percentile or less (P5), 47th through the 53rd percentile (P50), and the 95th percentile or higher (P95) for herd heritability were randomly selected. Yield or SCS from the selected herds were pooled for each percentile group and treated as separate traits. Records from P5, P50, and P95 were then analyzed with a 3-trait animal model. Heritability estimates were 23, 31, 26, and 8% higher in P95 than in P5 for milk yield, fat yield, protein yield, and SCS, respectively. The regression techniques successfully stratified individual herds by heritability, and additive genetic variance increased progressively, whereas permanent environmental variance decreased progressively as herd heritability increased.