Thanks very much for your response. Sorry for writing to you directly. Hereafter, I'll email to the R-Help list. I agree with all your comments and suggestions. My analysis will be descriptive type; purely observational as the studies are non-randomized studies. I have sample sizes and counts for each study. I'll first do the analysis taking 2 proportions. Then I'll try to use ordinal regression or a multinomial model. This is my first time doing meta analysis. I may have couple of questions later. If so , I will come back to this friendly R-Help group again. Thanks very much to Michael and you again. Dushanthi > From: wolfgang.viechtba...@maastrichtuniversity.nl > To: r-help@r-project.org; dushan...@bell.net > Date: Wed, 1 Aug 2012 10:58:49 +0200 > Subject: RE: "metafor" package, proportions: single groups wrt to a > categorical dependent variableþ > > Dear Dushanthi, > > Please keep your e-mails on the R-Help list, where Michael has already given > you some excellent advice. As Michael already explained, metafor can handle > proportions, but does not have any specific functionality for categorical > variables with more than 2 levels (at the moment). So, if it is logical and > possible to do so, you could collapse the levels of the categorical outcome > to 2 levels and then proceed with the proportions. To be specific, what you > need is the total sample size (let's call this variable ni) and the number of > "cases" (e.g., the number of people that improved) (let's call this variable > xi) for each study. For example: > > xi <- c(12, 18, 6) > ni <- c(30, 70, 40) > res <- rma(measure="PR", xi=xi, ni=ni) > res > forest(res) > > just to give you an idea. There are also various transformations that can be > applied to proportions and depending on your data, it may be more sensible to > work with one of these transformations. See "Proportions and Transformations > Thereof" under ?escalc. > > Of course, by doing so, you lose some information. More advanced would be to > use an ordinal regression or a multinomial model. > > Also, regarding your analysis plan -- while it is fine in principle, I hope > you are not planning to use the information obtained in this way to draw any > conclusions about the relative effectiveness of the two surgical procedures. > Based on what you wrote, it seems as if these are non-randomized studies > "with one or the other procedure applied." Therefore, any comparisons you > make would be purely observational and may be related to other variable that > confound any difference you may find. > > Best, > > Wolfgang > > -- > Wolfgang Viechtbauer, Ph.D., Statistician > Department of Psychiatry and Psychology > School for Mental Health and Neuroscience > Faculty of Health, Medicine, and Life Sciences > Maastricht University, P.O. Box 616 (VIJV1) > 6200 MD Maastricht, The Netherlands > +31 (43) 388-4170 | http://www.wvbauer.com > > > > -----Original Message----- > > From: Dushanthi Pinnaduwage [mailto:dushan...@bell.net] > > Sent: Tuesday, July 31, 2012 16:40 > > To: w...@metafor-project.org; Dushanthi Pinnaduwage > > Subject: "metafor" package, proportions: single groups wrt to a > > categorical dependent variableþ > > > > Dear Dr. Wolfgang Viechtbauer, > > > > I am using R version 2.15.0 and 'metafor' package version 1.6-0. Can this > > version of the package handle proportions from > > a categorical dependent variable for single studies? I mean can the > > package functions handle more than 2 proportions ? > > I know it can handle binary variables. > > > > If it can handle how do I set up my dataframe for the raw data from > > different studies? Also > > how do I give inputs, specially xi, mi (or ni) to the function escalc()? > > > > Thanks, > > Dushanthi [[alternative HTML version deleted]]
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