Augmenting the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data

摘要

We introduce an approach for ensuring empirical identification of the correlated trait-correlated method (CT-CM) model under a variety of conditions. A set of models are referred to as augmented correlated trait-correlated method (ACT-CM) models because they are based on systematically augmenting the multitrait-multimethod matrix put forth by Campbell and Fiske (1959). We show results from a Monte Carlo simulation study in which data characteristics lead to an empirically underidentified standard CT-CM model, but a well-identified fully augmented correlated trait-correlated method (FACT-CM) model. This improved identification occurs even for a model in which equality constraints are imposed on loadings on each trait factor and loadings on each method factora specific case shown to lead to an empirically underidentified CT-CM model.