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RE: st: Aren't distinct factors from factor analysis or PCA orthogonal to each other?


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Aren't distinct factors from factor analysis or PCA orthogonal to each other?
Date   Mon, 17 Aug 2009 14:01:45 -0400

Diana,
 
Yes, you may have to roll up your sleeves for this one, as I don't think it is automated in Stata, or any other program:

Jensen, A. R., & Weng, L. (1994). What is a good g? Intelligence, 18, 231-258.
 
Nelson, J.M., Canivez, G.L., Lindstrom, W., & Hatt, C.V. (2007). Higher-order exploratory factor analysis of the Reynolds Intellectual Assessment Scales with a referred sample. Journal of School Psychology, 45(4), 439-456.  
 
Cam
----------------------------------------
> From: JVerkuilen@gc.cuny.edu
> To: statalist@hsphsun2.harvard.edu
> Date: Mon, 17 Aug 2009 12:36:56 -0400
> Subject: RE: st: Aren't distinct factors from factor analysis or PCA orthogonal to each other?
>
> Diana Kornbrot wrote:
>
>>Is it possible to hierarchical EFA in stata?
>>Are there do files?
>
> What do you mean by hierarchical EFA? If you mean higher order factor analysis, i.e., imposing a factor structure on the factor covariance matrix, I suspect the answer is not at the present time. You could always extract the factor correlation matrix from an oblique rotation and work with the Schmid-Leiman transformations yourself.
>
> However, for a confirmatory model I suspect you could set this up in -gllamm- but I'd sure want to test it carefully on examples that I was certain about. I believe there are some examples of this in the PROC CALIS documentation in SAS/Stat, for instance.... Just checked. It's a replicated example of some data from Thurstone from R. P. McDonald (1985), Factor Analysis and Related Methods, LEA, , p.57, p.105.
>
> Jay
>
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