+ βXM, where βX is an unknown parameter to be estimated from the data, representing the magnitude of the moderating effect. If βX is significantly different from zero, there is evidence for a moderating effect. A similar logic follows for the βY and βZ pathways, which represent the extent to which a specific moderator variable alters the importance of common and unique environmental influences, respectively. In other words, the moderation model allows us to test whether the importance of additive genetic effects (a), common environmental effects (c), and unique environmental effects (e) are changing as a function of the measured variable. The pathway μ + βMM models main effects of the moderator variable on the outcome. Also included in this pathway are any gene–environment correlation effects between the moderator variable and outcome. Thus, any covariance between the moderator and the outcome is incorporated into the means model.
