The correction can be interpreted in standardized or unstandardized terms. In standardized terms, the proportion of variance attributable to A and E is rescaled relative to the corrected phenotypic variance; this correction increases the apparent influence of A compared to a model that does not correct for measurement error. The variance attributable to A and E sums to the total true variance in the outcome. Alternatively, one can interpret the unstandardized parameters; the estimate of E is lowered relative to a model that does not correct for measurement error, but the estimate of A is unaltered. We chose to interpret unstandardized parameter estimates. In the context of the correlated factors model, correcting measurement error has the effect of reducing e1 and e2 by an amount equal to the measurement error and increasing rE to indicate the amount of true environmental stability removed of idiosyncratic measurement error. However, the contribution of the environment to phenotypic stability (i.e., e1 × rE × e2) would remain unchanged, and therefore, the estimated phenotypic stability would also remain unchanged. Because increases in rE are counterweighted
