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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.

Diese Übung ist Teil des Kurses

Factor Analysis in R

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Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Run the EFA with six factors (as indicated by your scree plot)
EFA_model <- ___(bfi_EFA, ___)
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