A twin study including MZ and DZ twins who have been raised together can therefore provide estimates of A, C, or D, and E. C and D cannot be estimated simultaneously because these measures are negatively confounded with each other; shared environmental effects increase the correlation between DZ twins, whereas dominance effects increase the correlation between MZ twins (Evans, Gillespie, & Martin, 2002). These effects cannot be differentiated without additional data from twins reared apart, in which the effects of shared environment can be more directly modeled. Inclusion of broader kinships, such as children of twins, allows further estimation of additional factors such genetic and environment correlation. Sophisticated methodology such as structural equation modeling (Figure 2) provides the means to create more flexible models, for example, including data additional family members such as siblings, or modeling interactions of variance components with factors such as age. It also makes it possible to test whether particular variance components significantly improve the fit of the overall model.
