Biometric genetic studies of human populations typically analyze data on monozygotic (MZ) and dizygotic (DZ) twin pairs reared together to partition the variation of a trait within a sample of individuals into constituent variance components (VCs). These VCs typically consist of additive genetic (A), nonadditive genetic (D), or shared environmental (C) and child-specific environmental (E) influences. This last component also subsumes measurement error. Four key assumptions are involved in this approach: MZ twins are genetically identical, whereas DZ twins share on average 50% of their segregating alleles; MZ and DZ twin pairs share external environmental influences to the same extent; there is no correlation between members of twin pairs for E influences; and the total variance is the same in all individuals. Assuming a purely additive genetic model (D = 0), these assumptions predict the following statistics: phenotypic variance, A + C + E; MZ covariance, A + C; and DZ covariance, 0.5A + C. Estimates of these VCs may be obtained by using structural equation modeling (SEM) software, typically through maximum likelihood estimation.4,5 Differences in the relative impact of
