Re: st: disattenuated regression

[John Antonakis <John.Antonakis@unil.ch>]

Hi:

MPlus is a tad (well to be honest a mile) ahead when it comes to SEM 
models having categorical indicators. Of course, this Stata's sem 
version 1, so we hope to see some developments in Stata in the line of:

Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of 
alternative methods of estimation for confirmatory factor analysis with 
ordinal data. Psychological Methods, 9(4), 466-491.
Muthén, B. O. (1984). A general structural equation model with 
dichotomous, ordered categorical, and continuous latent variable 
indicators. Psychometrika, 49(1), 115-132.
Muthén, B. O., du Toit, S. H. C., & Spisic, D. (in press). Robust 
inference using weighted least squares and quadratic estimating 
equations in latent variable modeling with categorical and continuous 
outcomes. Psychometrika.

So, if you have such models it is best to use MPlus and the robust WLS 
(i.e., WLSMV) estimator.

As for your question, one can of course regress a latent variable on an 
observed variable. But it all depends on how you have done it (i.e., 
your full specification), by ensuring that the model is identified.

Best,
J.

__________________________________________

John Antonakis
Professor of Organizational Behavior
Director, Ph.D. program in Management

Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305
http://www.hec.unil.ch/people/jantonakis

Associate Editor
The Leadership Quarterly
__________________________________________


On 18.11.2012 17:33, 'Alim Beveridge wrote:
> Hi John,
> thanks again for your advice. I was thinking of doing this actually 
and have been teaching myself how to use sem in stata.
> However does it deal with dichotomous/categorical IVs, like Mplus 
does? It appears that it only does ML and ADF, and my sample size is too 
small for ADF (N = 210). Someone on statlist described how to create 
your own correlation matrix and then run sem on that. is that how I 
would have to do it?
>
> also when I put a regression path between an observed IV (say age or 
hours worked) and my latent DV, the model does not converge. These 
observed vars are only in the structural part of my syntax, not the 
measurement. Is this not allowed?
> thanks,
> 'Alim
>
> On 11/17/2012 5:18, John Antonakis wrote:
>> That's easy. Use -sem-
>>
>> It supports vce(robust) and vce(cluster id)
>>
>> See -help sem-. Note, if you have a single indicator of a latent the 
basic set up would be (for predicting y from proxy x of x*, the latter 
being the latent):
>>
>> (note latents are denoted in capitals in sem unless you specify 
otherwise)
>>
>> sem (X->x@1) (y<-X) , reliability(x .80) vce(cluster id)
>>
>> HTH,
>> John.
>>
>> __________________________________________
>>
>> John Antonakis
>> Professor of Organizational Behavior
>> Director, Ph.D. program in Management
>>
>> Faculty of Business and Economics
>> University of Lausanne
>> Internef #618
>> CH-1015 Lausanne-Dorigny
>> Switzerland
>> Tel ++41 (0)21 692-3438
>> Fax ++41 (0)21 692-3305
>> http://www.hec.unil.ch/people/jantonakis
>>
>> Associate Editor
>> The Leadership Quarterly
>> __________________________________________
>>
>>
>> On 16.11.2012 21:13, 'Alim Beveridge wrote:
>> > eivreg does what I want but it does not work with the vce option. 
it does not support svy either. Does anyone know how to do regression in 
Stata with correction for measurement error (like eivreg) AND cluster 
robust SEs  (like vce (cluster)).
>> >
>> > Thanks,
>> > 'Alim
>> >
>> > On 11/15/2012 4:01, Maarten Buis wrote:
>> >> On Thu, Nov 15, 2012 at 4:48 AM, 'Alim Beveridge wrote:
>> >>
>> >>> I would like to run disattenuated regression (DR) in Stata. I 
have not found
>> >>> a package that will do this for me.
>> >>>
>> >> Did you look at -help eivreg-?
>> >>
>> >> Hope this helps,
>> >> Maarten
>> >>
>> >> ---------------------------------
>> >> Maarten L. Buis
>> >> WZB
>> >> Reichpietschufer 50
>> >> 10785 Berlin
>> >> Germany
>> >>
>> >> http://www.maartenbuis.nl
>> >> ---------------------------------
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