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Absolute fit statistics

The absolute fit statistic reported in the CFA output is the likelihood ratio Chi-square test, which tests the hypothesis that the estimated model works as well as the null model. You've seen this fit statistic in the previous chapter, so you probably remember that the criteria for this test are very difficult to meet. Most models have a statistically significant result, which is not desirable here, since it means model fit is statistically worse.

After checking the absolute model fit statistics displayed by the summary() function, determine whether the likelihood ratio test is statistically significant.

Would the GFI for this model be considered acceptable?

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.

# Set the options to include various fit indices so they will print
options(___ = c("CFI", "GFI", "RMSEA", "BIC"))

# Use the summary function to view fit information and parameter estimates
___(theory_CFA)
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