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Re: st: How to interpret results from gllamm


From   Jurijs Ņikišins <jurijs.nikisins@lu.lv>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: How to interpret results from gllamm
Date   Tue, 06 Nov 2012 20:59:43 +0200

Thank you, Stas. 
Let me just ask again to be sure: are var(1) and var(2) intercepts and slopes only for the variable I treat as varying at level 2 (that is, new_demhist in my case)?
Do I understand you right?

On Tue 06/11/12 20:33 , Stas Kolenikov <skolenik@gmail.com> wrote:

> The parameters var(1) and var(2) are your random intercepts and> slopes. The individual level coefficients have the same> interpretation> as they would in a regular logistic regression: an increase of the> explanatory variable by 1 causes the linear prediction shift by {the> value of the regression coefficient}, and the change in probability> depends on the particular constellation of variables quantifiable> via> marginal effects (and -gllamm- may not work very well with -margins-> that otherwise provides a great interface to describe and visualize> these marginal effects).> -- > -- Stas Kolenikov, PhD, PStat (SSC)  ::  http://stas.kolenikov.name> -- Senior Survey Statistician, Abt SRBI  ::  work email kolenikovs> at> srbi dot com> -- Opinions stated in this email are mine only, and do not reflect> the> position of my employer> On Tue, Nov 6, 2012 at 12:01 PM, Jurijs Ņiki&scaron;ins  wrote:> > Hello,> > I'm a newcomer to both Stata and multilevel analysis and I have> some!
  general understanding of theory but implementing it in practice> is a real challenge for me so far, so I'd be really grateful for help> on interpreting results I get from gllamm.> > Using the European Social Survey 25-country dataset, I'm studying> the relationship between dichotomous outcome variable> demonstration_rec (whether a person took part in a demonstration last> year)> > and the following independent vars: gender, education, index of> attitudes to gender, cultural and income equality (resp. geq_mean,> ceq_mean, ieq_mean) and 4-rank democratic history variable> new_demhist denoting period that a country has been a stable> democracy.> > I treat new_demhist as a country-level variable, allowing it to> vary at a country level (i.e. trying to build a random-coefficient> model):> >> > gllamm demonstration_rec Gender_rec Education_rec geq_mean> ceq_mean ieq_mean i.new_demhist, family(binomial) link(logit)> i(country_rec) nrf(2) eqs(cntry_cons cntry_democr) nip(8)> > i.n!
 ew_demhist     _Inew_demhi_1-4     (naturally coded;> _Inew_demhi_1 om

itted)> >> ---------------------------------------------------------------------------> --------> demonstration_rec |      Coef.          Std. Err.           z     > P>|z|     [95% Conf. Interval]> >> ------------------+--------------------------------------------------------> -------->        Gender_rec |   .1956246          .0404499     4.84    > 0.000     .1163443    .2749049> >     Education_rec |   .2037315        .0162273    12.55    0.000  > .1719265    .2355365> >          geq_mean |    .2762476         .0232011    11.91    0.000> .2307744    .3217209> >          ceq_mean |     .1077089         .0102165    10.54    > 0.000     .0876849    .1277329> >          ieq_mean |      .3145431          .0246306    12.77   > 0.000     .2662681    .3628181> >     _Inew_demhi_2 |  -.4142843    .1031448    -4.02    0.000   > -.6164443   -.2121243> >     _Inew_demhi_3 |   .7189537    .0954098     7.54     0.000    > .5319539    .9059535> >     _Inew_demhi_4 |  -.0171796    .0929596!
     -0.18    0.853    > -.199377    .1650178> >             _cons |       -5.994235          .1476284   -40.60   > 0.000    -6.283581   -5.704889> >> ---------------------------------------------------------------------------> -------->  Variances and covariances of random effects> >> ---------------------------------------------------------------------------> ---> ***level 2 (country_rec)> >      var(1): .20405822 (.10364398)> >     cov(2,1): .00757171 (.01157615) cor(2,1): .03609139> >      var(2): .21568821 (.02322925)> >> ---------------------------------------------------------------------------> ---> My questions are:> >> > 1) How actually should I interpret var(1) and var(2)? Are they> individual- and country-level variance, or variances of intercept and> slope?> > 2) How do I interpret individual-level coefficients together with> level 2 variances and covariances?> >> > Thanks a lot in advance,> >> > Jurijs Nikisins> > Sociology PhD student, University of Latvia> >>!
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