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Re: st: Difference between factor score and linear prediction of latent variables after sem


From   Maarten Buis <maartenlbuis@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Difference between factor score and linear prediction of latent variables after sem
Date   Tue, 15 Oct 2013 08:52:28 +0200

The factor scores gives you the estimate of the latent variables based
on the measurement model, while the linear prediction gives you the
predicted values based on the structural model.

Hope this helps,
Maarten


On Mon, Oct 14, 2013 at 8:05 PM, Guillermo Montes
<gmontes@childrensinstitute.net> wrote:
> I estimated a sem model that regresses many observable predictors on two latent variables (SOC1 SOC2), each measured by 4 observable indicators.  Then, I used the post estimation commands to calculate both the factor scores and the linear predictions of the latent variables using the commands below.
>
> Predict Lat*, xblatent(SOC1 SOC2)
> Predict Fac*, latent(SOC1 SOC2)
>
> http://www.stata.com/manuals13/sempredictaftersem.pdf  The manual says factor scores are predicted values of latent variables.
>
>  What is the difference between a factor score and a linear prediction of a latent variable? The numbers are only correlated .7 or so in my case.
>
> Thanks
>
> Guillermo Montes Ph.D.
>
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-- 
---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
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