Multiple regression analysis of twin data.

Abstract

A multiple regression model for the analysis of twin data is described in which a cotwin's score is predicted from a proband's score and the coefficient of relationship (R=1.0 and 0.5 for identical and fraternal twin pairs, respectively). This model is especially appropriate for the analysis of data on twins in which one member of each pair has been selected because of a deviant score, e.g., low reading performance. When the model is fitted to such data, the partial regression of the cotwin's score on the coefficient of relationship provides a powerful test of the extent to which the difference between the mean for probands and that for the unselected population is heritable, i.e., a test for genetic etiology. By fitting an augmented model containing an interaction term to either selected or unselected data sets, direct estimates of heritability and the proportion of variance due to shared environmental influences can also be obtained (subject, of course, to the usual assumptions underlying twin analyses, e.g., a linear polygenic model, little or no assortative mating, and equal shared environmental influences for identical and fraternal twins).