Automated Fitting of Moderated Nonlinear Factor Analysis Through the 'Mplus' Program
Released Apr 12, 2018 by Veronica Cole
Automated generation, running, and interpretation of moderated nonlinear factor analysis models for obtaining scores from observed variables. This package creates 'Mplus' input files which may be run iteratively to test two different types of covariate effects on items: (1) latent variable impact (both mean and variance); and (2) differential item functioning. After sequentially testing for all effects, it also creates a final model by including all significant effects after adjusting for multiple comparisons. Finally, the package creates a scoring model which uses the final values of parameter estimates to generate latent variable scores.