Multiple regression analysis of twin data obtained from selected samples.
The multiple regression analysis of twin data in which a cotwin's score is predicted from that of a proband (the member of a twin pair selected because of a deviant score) and the coefficient of relationship provides a powerful test of genetic etiology (DeFries and Fulker: Behav Genet 15:467-473, 1985). Moreover, when an augmented model containing an interaction term is fitted to the same data set, direct estimates of heritability (h2) and the proportion of variance owing to shared environmental influences (c2) are also obtained. In the present paper, the expected partial regression coefficients estimated from these models are derived, and the flexibility of the general approach is illustrated. An extended model is formulated for the analysis of data from combined samples of affected and control twin pairs that yields tests for differential h2 and c2 in the two groups as well as pooled estimates of these parameters. The application of these models is illustrated by an analysis of data from reading-disabled and control twin pairs. Because of the ease, flexibility, and utility of the multiple regression analysis of twin data, it is an appealing alternative to more traditional model-fitting approaches.
D004200:Diseases in Twins; D004410:Dyslexia / Q000235:genetics; D004777:Environment; D030342:Genetic Diseases, Inborn / Q000209:etiology / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D012044:Regression Analysis; D014429:Twins, Dizygotic; D014430:Twins, Monozygotic