Two clarifying points are important to mention. First, this analysis uses the same information, but is slightly different from another commonly estimated longitudinal association, bivariate heritability. Rather than being reported in terms of raw units, bivariate heritability represents the proportion of a phenotypic correlation that is due to genetic effects. For example, if we observed that a trait displayed a phenotypic stability of .6 across time, a heritability of .5 at each time point and a genetic correlation of .8, the contribution of genetic influences to phenotypic stability would be .40 (i.e., √.5 × .8 × √.5), and the bivariate heritability would be .67 (i.e., [√.5 × .8 × √.5]/.6). The contribution to phenotypic stability has the useful property of being placed on the meaningful metric of phenotypic stability (which changes in magnitude across development) rather than being a proportion. Second, this type of analysis refers to the effective rather than objective stability of genetic and environmental effects (Turkheimer & Waldron, 2000). Objectively, one’s genotype (e.g., presence or absence of a specific polymorphism) or an environmental input (e.g., presence or
