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From |
Jurijs Ņikišins <jurijs.nikisins@lu.lv> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: How to interpret results from gllamm |

Date |
Tue, 06 Nov 2012 20:01:23 +0200 |

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/

**Follow-Ups**:**Re: st: How to interpret results from gllamm***From:*Stas Kolenikov <skolenik@gmail.com>

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