http://spssx-discussion.165.s1.nabble.com/Alpha-and-mean-inter-item-correlation-tp5715788p5715810.html
I said CFA and spelled out in parentheses the conditions
for "common-factor" analysis, namely, iteration to approximate
the communalities. "Confirmatory factors" probably need AMOS,
as you suggest. That wasn't on the table.
By the way: With those 69 variables, I might try a factoring where
I placed a fixed estimate of the communalities on diagonal, such
as 0.70, since h^2 estimates the reliability as an r. It might not give
a decent solution either, but that is one obvious way to improve
the chances for smaller loadings for some variables on some factors.
If the items are dichotomous, logic says the fill-in number is lower,
0.55 or even 0.40. I don't remember if I have ever tried that for
dichotomies -- For them, I've selected out the variables based
on mean-levels, and analyzed subsets, since dichotomies are
limited to having their best intercorrelations with other scores of
similar (or opposite) skew. Thus, stage 1 gives me a bunch of
tiny factors which I score up as simple means; and then I factor
analyze that much smaller number of scores.
--
Rich Ulrich
From:
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[hidden email]Subject: RE: Alpha and mean inter item correlation
Date: Tue, 23 Oct 2012 21:41:17 +0000
I don’t believe he will be able to do CFA with the standard SPSS package, will he? I thought that was only possible with the AMOS package.
I’m not sure I understand why the initial EFA didn’t work out. Certainly it makes no sense to run an EFA on pre-reduced groups, but running the EFA on all
items with an appropriate rotation (Varimax) should tell you if the items hang together in a reduced number of groups. Was this done? I was a bit confused on that matter.
Matthew J Poes
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