On Wed, 3 Aug 2005, Bernd Weiss wrote: > I am trying to replicate some multilevel models with binary outcomes > using R's "lmer" and "glmmPQL" and Stata's gllmm, respectively.
That's not going to happen as they are not using the same criteria. > The data can be found at <http://www.uni-koeln.de/~ahf34/xerop.dta>. > > The relevant Stata output can be found at <http://www.uni- > koeln.de/~ahf34/stataoutput.txt>. First, you will find the > unconditional model, i.e. no level1- or 2-predictor variables. The > second model contains some level 1-predictor variables > > My R file can be found at <http://www.uni-koeln.de/~ahf34/xerop.R>. > > Beside the fact that there is a difference between the estimates of > the intercept (unconditional model: R: -2.76459 and Stata: -2.698923) > I am especially interested in the level 2 variance. > > In Stata the level 2 variance is about 1.03, while in R it is 4.68. > > Using glmmPQL from package MASS again gives different results for the > level 2 variance component. What is meant by "Residual"? I thought > the level 1 variance is fixed to (pi^2)/3. Please read the book for which this is support software, as it definitely does not say that, and it does explain how such differences can occur. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html