Viechtbauer Wolfgang (STAT)
2007-Jun-19 12:52 UTC
[R] converting proc mixed to lme for a random effectsmeta-analysis
That was going to be my suggestion =) By the way, lme does not give you the right results because the residual variance is not constrained to 1 (and it is not possible to do so). Best, -- Wolfgang Viechtbauer ?Department of Methodology and Statistics ?University of Maastricht, The Netherlands ?http://www.wvbauer.com/ -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Bernd Weiss Sent: Tuesday, June 19, 2007 14:37 To: Lucia Costanzo Cc: r-help at stat.math.ethz.ch Subject: Re: [R] converting proc mixed to lme for a random effectsmeta-analysis On 19 Jun 2007 at 8:13, Lucia Costanzo wrote: Date sent: Tue, 19 Jun 2007 08:13:30 -0400 From: Lucia Costanzo <lcostanz at uoguelph.ca> To: r-help at stat.math.ethz.ch Subject: [R] converting proc mixed to lme for a random effects meta-analysis> I would like to convert the following SAS code for a Random Effects > meta-analysis model for use in R but, I am running into difficulties. > The results are not similar, R should be reporting 0.017 for the > between-study variance component, 0.478 for the estimated parameter > and > 0.130 for the standard error of the estimated parameter. I think it > is > the weighting causing problems. Would anyone have any suggestions or > tips? > > Thank you, > Lucia > > *** R CODE *** > studynum <-c(1, 2, 3, 4, 5) > y <-c(0.284, 0.224, 0.360, 0.785, 0.492) > w <-c(14.63, 17.02, 9.08, 33.03, 5.63) > genData2 <-data.frame(cbind(studynum, y, w,v)) > > re.teo<-lme(y~1, data=genData2, random =~1, method="ML", > weights=varFixed(~w)) > >What about using MiMa <http://www.wvbauer.com/downloads.html>? studynum <-c(1, 2, 3, 4, 5) y <-c(0.284, 0.224, 0.360, 0.785, 0.492) w <-c(14.63, 17.02, 9.08, 33.03, 5.63) ## without cbind(...) genData2 <-data.frame(studynum, y, w) mima(genData2$y, 1/genData2$w, mods = c(), method = "ML") Some output: - Estimate of (Residual) Heterogeneity: 0.0173 - estimate SE zval pval CI_L CI_U intrcpt 0.4779 0.1304 3.6657 2e-04 0.2224 0.7334 Looks like what you are looking for... HTH, Bernd ______________________________________________ R-help at 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 and provide commented, minimal, self-contained, reproducible code.