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Re: st: Difference between factor score and linear prediction of latent variables after sem
From
Guillermo Montes <[email protected]>
To
"<[email protected]>" <[email protected]>
Subject
Re: st: Difference between factor score and linear prediction of latent variables after sem
Date
Tue, 15 Oct 2013 11:00:38 +0000
It does. Thank you so much. G
> On Oct 15, 2013, at 2:54 AM, "Maarten Buis" <[email protected]> wrote:
>
> 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
> <[email protected]> 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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>> * http://www.ats.ucla.edu/stat/stata/
>
>
>
> --
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
>
> http://www.maartenbuis.nl
> ---------------------------------
>
> *
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