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.
Questo esercizio fa parte del corso
Factor Analysis in R
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# 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: ___
"