[R] Results of CFA with Lavaan
yrosseel
yrosseel at gmail.com
Thu Jun 9 11:19:12 CEST 2011
On 06/08/2011 11:56 PM, R Help wrote:
> Yes, that is the difference. For the last SEM I built I fixed the
> factor variances to 1, and I think that's what I want to do for the
> CFA I'm doing now. Does that make sense for a CFA?
If you have a latent variable in your model (like a factor in CFA), you
need to define its metric/scale. There are typically two ways to do
this: 1) fix the variance of the latent variable to a constant
(typically 1.0), or 2) fix the factor loading of one of the indicators
of the factor (again to 1.0). For CFA with a single group, it should not
matter which method you choose. The fit measures will be identical.
Lavaan by default uses the second option. If you prefer the first
(fixing the variances), you can simply add the 'std.lv=TRUE' option to
the cfa() call, and lavaan will take care of the rest.
> I'll try figuring out how to do that with lavaan later, but my model
> takes so long to fit that I can't try it right now.
You can use the 'verbose=TRUE' argument to monitor progress. You may
also use the options se="none" (no standard errors) and test="none" (no
test statistic) to speed things up, if you are still constructing your
model. Or the model does not convergence, but I should see both the
model and the data to determine the possible cause.
Hope this helps,
Yves Rosseel
http://lavaan.org
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