This is a problem that can only be done on a SEM program such as Amos. As I understand your message, you are asking is whether a two factor model fits better
than a one factor model. And, you propose that factor 1 is composed of items A, B, D and factor 2 is composed of items C, E, F. (You can force a two factor solution but you can not control item-to-factor assignment.) The one factor model should have a df of
9 and the two factor model should have a df of 8. I think, but I may be wrong, that if you constrain the factor variances in the two factor model to be equal, you will have the correct nested model test.
Gene Maguin
From: SPSSX(r) Discussion [mailto:[hidden email]]
On Behalf Of Deena Isom
Sent: Monday, January 20, 2014 4:39 PM
To: [hidden email]
Subject: Fwd: Latent Variable Analysis: CFA, EFA, and IRT?
---------- Forwarded message ----------
From: Deena Isom <[hidden email]>
Date: Mon, Jan 20, 2014 at 4:38 PM
Subject: Latent Variable Analysis: CFA, EFA, and IRT?
To: [hidden email]
Hello List,
I'm trying to determine which analytical strategy is best for a current project, and if any are adequately conducted in SPSS or if another stats package is needed.
I'm trying to assess if two latent constructs are truly distinct, when in most literature items assessing each they are measured together in one scale..... I believe this is best done with exploratory factor analysis to see how different
questions load of different factors, but if I believe they are different, would confirmatory factor analysis better serve these purposes - force their loadings? Also, can either of these really be fully conducted in SPSS and provide information about fit
and so forth? And finally, could item response theory help distinguish which questions measure which concepts? Honestly, I'm still confused by IRT.
Thanks in advance for your insight. Hope you had a wonderful holiday!
--
~Deena
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~Deena
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