Date: Thu, 12 Jun 2008 13:24:02 0400
ReplyTo: Hideko Bassett <hhamada@gmu.edu>
Sender: "SPSSX(r) Discussion" <SPSSXL@LISTSERV.UGA.EDU>
From: Hideko Bassett <hhamada@gmu.edu>
Subject: Comparing 2factor and 3factor models
InReplyTo: <7.0.1.0.2.20080612123640.03b0d668@mindspring.com>
Contenttype: text/plain; charset=USASCII; format=flowed; delsp=yes
Hi,
I'm using AMOS to compare fitness of 3factor and 2factor models. Our
theoretically based model consists of 3 factors. By holding one of the
covariances between 2 latent variables (setting it as "1"), I believe
I can create 2factor model nested in 3factor model. Then, there 2
reference variables (set regression weight as "1") in the combined
latent variables (one reference variable per latent variable). My
question is that when I hold one of the covariances, do I have to
change regression weight of one reference variables? I'm wondering if
by holding the covariance between 2 latent variables is the same as
one latent variable, then, there shouldn't be 2 reference variables in
it. So I tried to run analysis on this 2factor model in two different
way. One is to leave 2 reference variables as they are, and the other
is to release one of the reference variables. The two results I got
were dramatically different (the first one had chisquare = 85 and
significant, and the latter one had chisquare = 21 and not
significant).
As you can see, I'm vary new to the world of SEM and AMOS, so any help
would be appreciated.
Also, our data is not normally distributed, so I would like to get
robust chisquare, but I'm not sure how to do it with AMOS. Does
anyone have suggestions on which estimation method to use with non
normally distributed data?
Thank you very much.
Hideko
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