Interpreting the results
As before, you'll be interested in items' factor loadings and individuals' factor scores. These will be interpreted in the same way, but since your EFA is multidimensional, you’ll get results for each factor.
Remember, an item's loadings represent the amount of information it provides for each factor. Items’ meaningful loadings will be displayed in the output. You’ll notice that many items load onto more than one factor, which means they provide information about multiple factors. This may not be desirable for measure development, so some researchers consider only the strongest loading for each item.
Each examinee will have a factor score for each factor, so that the matrix won't include blanks. However, examinees with missing data will receive NA scores on all factors.
This exercise is part of the course
Factor Analysis in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Run the EFA with six factors (as indicated by your scree plot)
EFA_model <- ___(bfi_EFA, ___)