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From | Stas Kolenikov <skolenik@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: How to interpret results from gllamm |
Date | Tue, 6 Nov 2012 12:33:16 -0600 |
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 Ņikišins <jurijs.nikisins@lu.lv> 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.new_demhist _Inew_demhi_1-4 (naturally coded; _Inew_demhi_1 omitted) > ----------------------------------------------------------------------------------- > 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 > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/