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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: SV: Latent variable DVs in gllamm |

Date |
Wed, 11 Feb 2009 16:52:56 -0600 |

If you have three levels, then you would need more equations -- one for each level. That's where your error message comes from. How you want to incorporate other leves is up to you though -- as random effects, random slopes, whether they affect the lower levels latent variables -- pretty much any configuration might be defensible, just look at what makes sense for your problem and in your discipline. On 2/11/09, Rahsaan Maxwell <rahsaan@polsci.umass.edu> wrote: > Thanks, this definitely helps. > > Does it look like I have set it up correctly? > > Because I have two questions. > > 1) If I run the following code I get this error message, which I am not sure I > understand: > > 1 equations specified: response, need 2 > > 2) Also, if I want to run a multilevel model with variables that analyze both > the individual and the neighborhood level, is it correct to include the > neighborhood grouping variable 'neighid' as I have done below? > > Thanks, > > -Rahsaan > > sort council courts police > gen id=_n > expand 3 > sort id > qui by id: gen response=_n > gen item1=response==council > gen item2=response==courts > gen item3=response==police > > > eq response : item1 item2 item3 > > eq latent : x1...x4 > gllamm response, i(id neighid) eq(response) geq(latent) link(ologit) > > > > > > > Quoting Stas Kolenikov <skolenik@gmail.com>: > > > You expand the data to create a single variable, let's call it > > -response-. For each original observation identified by variable > > called -id-, then you will need to create three dummy variables, say > > -item1-, -item2- and -item3-, to keep track of where that response > > came from. Then your model will essentially look like > > > > eq response : item1 item2 item3 > > eq latent : all regressors for the latent variable > > > > gllamm response, id( id ) eq( response ) geq( latent ) link() family() > > > > The -eq- options says what is the pattern of the loadings of the > > latent variable on the observed ones, and -geq- says what is the > > structural model for that latent variable -- in your case, your > > regression. > > > > On 2/11/09, Rahsaan Maxwell <rahsaan@polsci.umass.edu> wrote: > > > Thanks for the response. I see that I need to expand the data but I'm not > > sure > > > how to then combine the three observed variables into one multivariate > > > response? > > > > > > From what I can tell, section 8.4 in the gllamm manual is the closest to > > my > > > situation but it looks like they are regressing y on the different items > > that > > > comprise the latent variable, whereas I want to be regressing the items of > > the > > > latent variable on other variables. Or is that a necessary first step to > > get > > > the factor loadings? In which case how do I define y? That doesn't seem > > to be > > > addressed in the manual. > > > > > > Thanks, > > > > > > > > > -Rahsaan > > > > > > > > > Quoting Mads Meier Jæger <Mads@sfi.dk>: > > > > > > > Rahsaan, > > > > > > > > This can be done in gllamm by expanding the data so that the three > > observed > > > > variables (trust in police, etc.) form a multivariate response for each > > > > individual, and then by using a random effect to model the latent DV. > > You > > > > need to expand the data to "trick" gllamm into treating the three > > observed > > > > variables as a multivariate response, see chapter 4 and 8 in the gllamm > > > > manual. It should be easy enough also to include more random effects to > > > > account for additional multilevel (neighbourhood, etc.) clustering. You > > could > > > > also use eqs() to model covariate effects on the latent DV. > > > > > > > > Mads > > > > > > > > > > > > > > > > -----Oprindelig meddelelse----- > > > > Fra: owner-statalist@hsphsun2.harvard.edu > > > > [mailto:owner-statalist@hsphsun2.harvard.edu] På vegne af Rahsaan > > Maxwell > > > > Sendt: 11. februar 2009 06:49 > > > > Til: statalist@hsphsun2.harvard.edu > > > > Emne: st: Latent variable DVs in gllamm > > > > > > > > Does anyone know if it is possible to build a multi-level mixed effects > > model > > > > with a latent DV using glamm? > > > > > > > > I have a unobserved response variable (political trust) that is > > comprised of > > > > three observed variables (trust in police, trust in government, trust in > > > > politicians). I am trying to run a multi-level model with fixed effects > > IVs > > > > at > > > > the individual and neighborhood level and a random intercept for the > > > > neighborhood grouping level. > > > > > > > > However, I cannot figure out how to construct the DV as a latent > > variable. I > > > > have been trying to use the eqs function but that does not seem to work. > > > > > > > > Thanks, > > > > > > > > -Rahsaan > > > > > > > > > > > > Rahsaan Maxwell, Ph.D. > > > > Assistant Professor > > > > Department of Political Science > > > > University of Massachusetts, Amherst > > > > > > > > Postdoctoral Fellow > > > > Transatlantic Academy > > > > German Marshall Fund of the United States > > > > http://rahsaanmaxwell.googlepages.com > > > > * > > > > * For searches and help try: > > > > * http://www.stata.com/help.cgi?search > > > > * http://www.stata.com/support/statalist/faq > > > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > > > > > > > * > > > > * For searches and help try: > > > > * http://www.stata.com/help.cgi?search > > > > * http://www.stata.com/support/statalist/faq > > > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > > > > > > > > Rahsaan Maxwell, Ph.D. > > > Assistant Professor > > > Department of Political Science > > > University of Massachusetts, Amherst > > > > > > Postdoctoral Fellow > > > Transatlantic Academy > > > German Marshall Fund of the United States > > > http://rahsaanmaxwell.googlepages.com > > > * > > > * For searches and help try: > > > * http://www.stata.com/help.cgi?search > > > * http://www.stata.com/support/statalist/faq > > > * http://www.ats.ucla.edu/stat/stata/ > > > > > > > > > -- > > Stas Kolenikov, also found at http://stas.kolenikov.name > > Small print: I use this email account for mailing lists only. > > > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > > Rahsaan Maxwell, Ph.D. > Assistant Professor > Department of Political Science > University of Massachusetts, Amherst > > Postdoctoral Fellow > Transatlantic Academy > German Marshall Fund of the United States > http://rahsaanmaxwell.googlepages.com > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: SV: Latent variable DVs in gllamm***From:*Rahsaan Maxwell <rahsaan@polsci.umass.edu>

**References**:**st: Latent variable DVs in gllamm***From:*Rahsaan Maxwell <rahsaan@polsci.umass.edu>

**st: SV: Latent variable DVs in gllamm***From:*Mads Meier Jæger <Mads@sfi.dk>

**Re: st: SV: Latent variable DVs in gllamm***From:*Rahsaan Maxwell <rahsaan@polsci.umass.edu>

**Re: st: SV: Latent variable DVs in gllamm***From:*Stas Kolenikov <skolenik@gmail.com>

**Re: st: SV: Latent variable DVs in gllamm***From:*Rahsaan Maxwell <rahsaan@polsci.umass.edu>

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