WLSMV better fit with non-ordered variables

[Emanuele]

Hi,

I am running CFA with a set of items on a 5-point Likert, with WLSMV and ordinal variables ("ordered = c"()), but model fit is not satisfactory. Similar model fit with MLR and MLM. However, when I run WLSMV without declaring variables as ordered, model fit is excellent. Would it make sense to accept model fit with WLSMV as run on a continuous variables?

Thank you

Emanuele

[Henrique Oliveira]

Hi,

My data was 24 itens, all using a five points Likert scale. I used the option 'ordered=TRUE' in cfa command, instead of 'ordered = c()':

myModel.v1.fit <- cfa(myModel.v1, data=my.data, std.lv=TRUE, ordered=TRUE)

The estimator DWLS was automatically chosen (there is no need to specify it)

Best,

Henrique

[Emanuele Fino]

Hello,

Thank you very much! I tried and I've got the same result as with ordered = c(). I've read other posts and apparently it's not a good idea to assume continuous data with WLSMV, so I guess I've got no other options but to accept that. It's a shame because my model fits great with just estimator = WLSMV. I would be interested to understand what does lavaan compute when neither ordered = c() nor ordered = TRUE are provided, anyway. 

Best wishes 

Emanuele 

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[Guido]

I think this article may be of interest for you concerning your question: https://pubmed.ncbi.nlm.nih.gov/26174714/

By the way if you don't declare your variables as ordered it is my understanding that Lavaan automatically uses ML in stead of WLSMV. 

Cheers, G

[Henrique Oliveira]

Hi,

Very nice reference. Thanks.

I first used SPSS with ML but the reviewer refused these approach and told me to use Lavaan.

Fortunately for me, I have now best fit results using DWLS in Lavaan.

All the best,

Henrique

[Emanuele Fino]

Hi,

Thank you very much for the useful reference. I totally agree with Henrique, it is really great that we can have a range of estimators with Lavaan, including DWLS / WLSMV! Sorry for my delay in replying, I went back to my analysis and I tried what Guido said. My results suggest that if you don't declare your variables as ordered but include estimator = "WLSMV" you won't get ML, though, as results differ from when I use estimator = "ML".Interestingly, if I declare my indicators as ordered and use WLSMV, I get a very high CFI.scaled (.997) but unsatisfactory RMSEA.scaled (.137). The same did not happen when I (erroneously, I guess) ignored the ordered command.

Best wishes

Emanuele

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