Structural equation modelling in developmental psychiatry

Annotation: structural equation models in developmental research.

Component-based Structural Equation Modelling

Two complementary schools have come to the fore in the field of Structural Equation Modelling (SEM): covariance-based SEM and component-based SEM. The first approach has been developed around Karl Jöreskog and the second one around Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane have proposed a new component-based SEM method named Generalized Structured Component Anal...

Structural Equation Modelling for small samples

Covariance-based SEM is usually used with an objective of model validation and needs a large sample (what is large varies from an author to another: more than 100 subjects and preferably more than 200 subjects are often mentioned). Component-based SEM is mainly used for score computation and can be carried out on very small samples. A research based on 6 subjects has been published by Tenenhaus...

Structural equation modelling: Adjudging model fit

For journal editors, reviewers, and readers of research articles, structural equation model (SEM) fit has recently become a confusing and contentious area of evaluative methodology. Proponents of two kinds of approaches to model fit can be identified: those who adhere strictly to the result from a null hypothesis significance test, and those who ignore this and instead index model fit as an app...

Twin-singleton differences in brain structure using structural equation modelling.

Twin studies are important to investigate genetic influences on variation in human brain morphology in health and disease. However, the twin method has been criticized for its alleged non-generalizability due to differences in the intrauterine and family environment of twins, compared with singletons. To test whether twin-singleton differences complicate interpretation of genetic contributions ...