Remove loadings to improve fit
Removing weak item/factor relationships will typically improve your model fit because you're estimating only meaningful parameters. However, when removing loadings, you want to be sure you are okay with removing the item from your measure. Removing an item's loading effectively means that item is no longer included in your measure, and scores on that item won't be considered in the analysis.
Deze oefening maakt deel uit van de cursus
Factor Analysis in R
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Remove the weakest factor loading from the syntax
theory_syn_del <- "
AGE: A1, A2, A3, A4, A5
CON: C1, C2, C3, C4, C5
EXT: E1, E2, E3, E4, E5
NEU: N1, N2, N3, N4, N5
OPE: ___
"