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Date:         Thu, 12 Jun 2008 13:24:02 -0400
Reply-To:     Hideko Bassett <hhamada@gmu.edu>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Hideko Bassett <hhamada@gmu.edu>
Subject:      Comparing 2-factor and 3-factor models
Comments: To: Richard Ristow <wrristow@mindspring.com>
In-Reply-To:  <7.0.1.0.2.20080612123640.03b0d668@mindspring.com>
Content-type: text/plain; charset=US-ASCII; format=flowed; delsp=yes

Hi, I'm using AMOS to compare fitness of 3-factor and 2-factor 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 2-factor model nested in 3-factor 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 2-factor 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 chi-square = 85 and significant, and the latter one had chi-square = 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 chi-square, 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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