A DeFries and Fulker Regression Model for Genetic Nonadditivity
Waller NG
Department of Psychology, University of California, Davis 95616.
Behavior Genetics, 24(2):149-153 (1994)
Abstract
Parameter estimates from the DeFries and Fulker [(DF) Behav. Genet. 15:462-473,
1985] regression method can be greater than unity or less than zero. This occurs when
the monozygotic correlation is greater than twice the dizygotic correlation. Sensible
values can be obtained in these cases by fitting a constrained DF model that estimates
genetic and nonshared environmental variance components only. In this article I
demonstrate that the original Df model yields positively biased heritability estimates and
negatively biased estimates of shared environmentality when data are significantly
influenced by genetic nonadditivity. The magnitude of the bias is algebraically expressed.
I then describe a simple regression equation that provides unbiased estimates of the
standardized additive and dominance genetic variance components. Results of a study of
6 million twin pairs from the Monte Carlo Twin Registry demonstrate that the DF
additive and dominance genetic parameter estimates are virtually identical to those
obtained by maximum-likelihood procedures. Finally, I derive the expectations for the
constrained DF model and show that the genetic parameter estimates from this model
are negatively biased estimates of broad-sense heritability.
Variance component linkage analysis