Behavioral genetic methods conceptualize measurement error in a slightly different manner. Because measurement error is unsystematic, it serves to make siblings different from one another and is therefore a component of the nonshared environment. Typically, the variance of a measured outcome in a twin model is assumed to be zero as the A and E latent factors represent the total decomposition of this variance. To correct the E component for a known amount of measurement error, the phenotype can be specified to have a set amount of residual (error) variance not explained by A or E. Thus, the remaining E variance represents true environmental effects on the outcome. Figures 1 and 2 explicitly depict this specification by showing that the phenotype’s residual variance is zero in the standard model (this specification is often left out of depictions of behavioral genetic models) and as 1- reliability for a model in which measurement error is corrected.
