Eigenvalues in ESEM PreviousNext
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 Jeremy Miles posted on Tuesday, April 14, 2009 - 1:24 pm

I wanted to try to obtain or calculate eigenvalues when using the ESEM approach. Is there a way of doing that, or can you point me towards the formula?


 Linda K. Muthen posted on Thursday, April 16, 2009 - 5:58 pm
You can obtain the eigenvalues using TYPE=EFA. It's the usual formula for the eigenvalues of the sample correlation matrix with ones on the diagonal as shown in a factor analysis book.
 Jeremy Miles posted on Friday, April 17, 2009 - 10:40 am
Thanks - I wondered if it were possible to get them from ESEM, when I have additional parameters (such as theoretically based correlated errors) which I can't model with EFA. If it's possible, I wanted to plot a scree plot with and without additional some additional regression parameters.

The idea of this is to show that a multi-factor solution is an artifact of a couple of very similar items - specifically that item order influences answers.

I tried things like calculating the eigenvalues using the residuals or the sums of squared (standardized) loadings, but I don't think the 'true' sum of eigenvalues is the number of items, as the additional regression parameters. The eigenvalue of the first factor extracted is lower when there are regression parameters in there, but I want to scale that up, to make it a proportion of the sum of the eigenvalues.

Does that make sense? If it does, is it possible, or do I need to think of a different way to make my point.


 Bengt O. Muthen posted on Friday, April 17, 2009 - 1:33 pm
Sounds like you want eigenvalues for a model-estimated covariance (or corr) matrix. You can print the matrix and then submit it to a program getting eigenvalues. But I'm not sure that answers your question - seems like your point is more easily made by working with say BIC as a result of using fewer factors.
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