[R] meta / lme

[Viechtbauer Wolfgang (STAT)]

Hello Stephen,

As far as I know, the meta package will not allow you to include moderator variables in the model. However, I have written a script for R/S-Plus that will allow you to fit such models (essentially, these are mixed-effects models with a random intercept). You can find the script here: http://www.wvbauer.com/downloads.html

Specifically, if you scroll down a bit, you will find the "mima" function with a tutorial that explains how it can be used. I hope you find this useful.

Best wishes,

-- 
Wolfgang Viechtbauer 
 Department of Methodology and Statistics 
 University of Maastricht, The Netherlands 
 http://www.wvbauer.com/

-- 
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 Stephen
> Sent: Sunday, March 12, 2006 11:55 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] meta / lme
> 
> Hi
> 
> 
> 
> I'm conducing a meta-analysis using the meta package.
> 
> 
> 
> Here's a bit of code that works fine -
> 
> tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2,
> 
> samplesize.1, pctdropout.1, sddropout.1,
> 
>          data=Dataset, sm="WMD")
> 
> 
> 
> I would now like to control for a couple of variables (continuous and
> categorical) that aren't in the equation.
> 
> 
> 
> Is meta inappropriate for these purposes? If so, based on the above
> code, how would I add variables to the equation?
> 
> 
> 
> Perhaps I should use lme weighting on sample size?
> 
> 
> 
> Thoughts appreciated
> 
> 
> 
> Thanks S.
> 
> 
> 
> PS
> 
> > version
> 
>          _
> 
> platform i386-pc-mingw32
> 
> arch     i386
> 
> os       mingw32
> 
> system   i386, mingw32
> 
> status
> 
> major    2
> 
> minor    2.1
> 
> year     2005
> 
> month    12
> 
> day      20
> 
> svn rev  36812
> 
> language R