Common Pathway Model

Abstract

Abstract While traditional multivariate statistical methods can describe correlational patterns of a set of variables (e.g., psychiatric symptoms or problem behaviors in children), they cannot provide insight into why certain symptoms or behaviors tend to co‐occur in a population. This can be achieved using methods of multivariate genetic analysis . In multivariate genetic models, two main classes can be distinguished, which differ in the way the common factors are assumed to influence the different observed variables. The way unique factors influence the observed variables is the same in both classes. The first class of models is referred to as common pathway or psychometric models. Common genetic and environmental factors influence all observed variables via a single psychometric factor, or underlying latent liability. This factor is identical to the factor derived from higher order phenotypic factor analyses, with the difference that twin data allows estimation of the relative importance of genetic and environmental effects of this factor. The second class of models is referred to as independent pathway models or biometric models, where the common genetic and environmental factors influence the observed variables directly, without an intermediate higher order factor. As a result, the common genetic and environmental factors do not necessarily cause similar groupings of variables.