DeFries-Fulker multiple regression method
(DeFries & Fulker, 1985, 1988)
Click the underlined links for a picture of each step in the analysis
The DF model is based on the differential regression to the mean of MZ and DZ cotwins when proband twins are selected for extreme scores on a phenotype.
If the proband deficit is due solely to nonshared environmental influences (for example, an early traumatic brain injury), then the cotwin shares none of these etiological influences with the proband. Therefore, the means of both MZ and DZ cotwins should regress to the population mean.
If the proband deficit is due in part to shared environmental influences (for example, family nutrition), then both the MZ and DZ cotwins are also exposed to the same shared environmental influences as the probands. Because both MZ and DZ twin pairs share 100% of the shared environmental variance, the means of both MZ and DZ cotwins should regress an equal distance back to the population mean.
If the proband deficit is due to genetic influences, both the MZ and DZ cotwins will regress back to the population mean, but the DZ cotwins will regress farther.
The basic DF regression model is as follows:
C = B1 P + B2 R + K
where C is the expected cotwin score, P is the proband score, R is the coefficient of relationship (1 for MZ pairs, 0.5 for DZ pairs), and K is the regression constant. The B1 coefficient represents the partial regression of the cotwin score on the proband score, and provides a measure of twin resemblance irrespective of zygosity. The B2 parameter represents the partial regression of the cotwin score on the coefficient of relationship, and after appropriate transformation of the data provides a direct estimate of the heritability of extreme scores on the trait under consideration (h2g). After adjustment of the standard errors of the regression coefficients to correct for the double entry of concordant pairs, the significance of the B2 parameter provides a statistical test of the extent to which extreme scores are attributable to genetic influences.