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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.

This exercise is part of the course

Factor Analysis in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# 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: ___
"
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