This technique is a form of structural equation modeling, distinguished from the classical method by being component-based rather than covariance-based.

More generally, principal component analysis can be used as a method of factor analysis in structural equation modeling.

Structural equation modeling was used to test three alternative explanatory models to understand why the rationale produced such benefits:

Common frameworks for causal inference are structural equation modeling and Rubin causal model.

A beginner' guide to structural equation modeling (3rd ed.)

More recently, structural equation modeling and path analysis represent more sophisticated approaches to working with large covariance matrices.

Simple inferential statistics are preferred (79%) instead of, for example, structural equation modeling (17%).

The comparative efficacy of imputations methods for missing data in structural equation modeling.

However, new statistical methods like structural equation modeling are being used to test for potential causal relationships in this type of data.

OpenMx is an open source program for extended structural equation modeling.