Abstract
Abstract The goal of multivariate genetic analysis is to estimate the causes of genetic and environmental covariation between phenotypes. As with univariate modeling, when data from genetically informative relatives such as twins are available, the genetic and environmental components of covariation can be separated by a technique which is analogous to factor analysis (Martin & Eaves,). This is achieved by making use of the additional information in the cross‐correlations between relatives for different traits (or same traits measured at different times) and can allow researches to estimate the extent to which genetic and environmental influences are shared in common by several traits or are trait specific. The various forms of multivariate analyses covered in this section include the Cholesky decomposition, common and independent genetic pathway models, and genetic simplex modeling. This section will give the reader an appreciation for the flexibility of SEM approaches to address more complicated questions beyond simpler univariate decompositions.
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