Multiple Regression Analysis of Twin Data: Etiology of Deviant Scores versus Individual Differences

Abstract

The multiple regression analysis of twin data in which a cotwin's score is predicted from a proband's score and the coefficient of relationship (the basic model) provides a statistically powerful test of genetic etiology. When an augmented model that also contains an interaction term is fitted to the same data set, direct estimates of heritability (h²) and the proportion of variance due to shared environmental influences (c²) are obtained. A simple transformation of selected twin data prior to regression analysis facilitates direct estimates of h²_g (an index of the extent to which the difference between the mean of probands and that of the unselected population is heritable) and a test of the hypothesis that the etiology of deviant scores differs from that of variation within the normal range.