Solved – How to extract “MLR” fit measures generated by the Lavaan package of R

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I am estimating some Confirmatory Factor Analysis (CFA) models using the Lavaan package and I hoping to extract the fitMeasures to export out of the model to a spreadsheet. This is easily done using the fitMeasures command, but it automatically defaults to exporting the "ML" fit measures, even if the model was run using "MLR". Is there a way to extract these fitMeasures from the robust model?

Here is my example script:

## The famous Holzinger and Swineford (1939) example
HS.model <- 'visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9'
fit <- cfa(HS.model, data=HolzingerSwineford1939, estimator="MLR", std.lv=TRUE)
fitMeasures(fit, fit.measures = c("chisq", "cfi", "rmsea", "aic"))

Running the summary reveals that fitMeasures produces "ML" fit measures, not Robust fit measures:

summary(fit, standardized=TRUE, fit.measures=TRUE, rsquare=TRUE)

Is there a way I can obtain the Robust fit measures? Thanks in-advance for your help!

I think I found the solution to this (below):

I used the following in my example above to extract the robust (scaled) fit measures:

fits<-inspect(fit, "fitMeasures")
fits[c(5:7,24,44,34)]

I hope it helps someone out there and please let me know if there is a better way to accomplish this!

Best Answer

Here is another option that is line with your approach to getting standard fit indices: 

fit.scaled<-c("chisq.scaled", "cfi.scaled", "rmsea.scaled", "aic")    
fitMeasures(fit, fit.scaled)

That should give you the specific scales you want. You can include as many indices as you want to the fit.scaled object. You can use fitMeasures(fit) to get a display of all possible fit indices you can request of the model.

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