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 ConsultantsOn 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!
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~Deena
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~Deena
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Art Kendall
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