If you have a strong background, and good reasoning then CFA is
the only way to be sure that your model fits.
However, that requires either expensive extra software or using
ad hoc software.
Otherwise, if you have a good may many more cases than variables
(10x?), a PAF with varimax rotation will give you a good shot at
scales that have discriminative validity. Be sure to keep only
items that load cleanly if you retain more than 1 factor.
It is possible that you will need to generate a larger items
pool if you want to have items that measure more constructs.
Parallel analysis will help you determine the number of factors
to retain.
Any thing more specific would depend on knowing the actual
items, the eigenvalues, etc.
Art Kendall
Social Research Consultants
On 1/20/2014 4:46 PM, Deena Isom [via SPSSX Discussion] wrote:
---------- 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
--
~Deena
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