Abstract
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 factor—a specific case shown to lead to an empirically underidentified CT–CM model.
Original language | English (US) |
---|---|
Pages (from-to) | 798-818 |
Number of pages | 21 |
Journal | Structural Equation Modeling |
Volume | 23 |
Issue number | 6 |
DOIs | |
State | Published - Nov 1 2016 |
Keywords
- construct validity
- correlated trait–correlated method model
- method effects
- method variance
- multitrait–multimethod models
ASJC Scopus subject areas
- General Decision Sciences
- Modeling and Simulation
- Sociology and Political Science
- Economics, Econometrics and Finance(all)