Recalculating df in MGCFA testing
Plase cite as follows: Schroeders, U. & Gnambs, T. (in press). Degrees of freedom in multi-group confirmatory factor analysis: Are models of measurement invariance testing correctly specified? European Journal of Psychological Assessment.
|A. Number of indicators||C. Number of cross-loadings||E. Number of resid. covar.|
|B. Number of factors||D. Number of ortho. factors||F. Number of groups|
|A||Indicates the number of indicators or items.|
|B||Indicates the number of latent variables or factors.|
|C||Indicates the number of cross-loadings. For example, in case of a bifactor model the number equals twice the number of indicators (A).|
|D||Indicates the number of orthogonal factors. For example, in case of a nested factor model with six indicators loading on a common factor and three items additionally loading on a nested factors, you have to specify 2 factors (B) and 1 orthogonal factor (D).|
|E||Indicates the number of residual covariances.|
|F||Indicates the number of groups.|
- Beaujean, A. A. (2014). Latent variable modeling using R: a step by step guide. New York: Routledge/Taylor & Francis Group.
- Millsap, R. E. & Olivera-Aguilar, M. (2012). Investigating measurement invariance using confirmatory factor analysis. In R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling (pp. 380-392). New York: Guilford Press.
- Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: Guilford Press.