Hi Michael,
The supervisorfor my Master'sThesis told me that my means are the effect size and cause of this I have to take figure 1 for all standard deviations. So I hope that was the right information. ________________________________ From: Michael Dewey <i...@aghmed.fsnet.co.uk> lfgang.viechtba...@maastrichtuniversity.nl>; Michael Dewey <i...@aghmed.fsnet.co.uk>; "r-help@r-project.org" <r-help@r-project.org> Sent: Wednesday, January 23, 2013 10:22 AM Subject: Re: [R] dummy encoding in metafor At 08:30 23/01/2013, Alma Wilflinger wrote: > Dear Wolfgang and Michael, > [[elided Yahoo spam]] > > Concerning the Variance: I took the variance I used for CMA (which is always > 1), so I think it should be the right one. It seems unlikely to me that the variance from each study would be the same although I suppose it could be possible. Are you sure you are supplying the right values to CMA? > Thank you for noticing and mentioning though :) > > I really appreciate how helpful you both are. > > best, > Alma > > > > From: Viechtbauer Wolfgang (STAT) > <wolfgang.viechtba...@maastrichtuniversity.nl> > To: Michael Dewey <i...@aghmed.fsnet.co.uk>; Alma Wilflinger > <alma_an...@yahoo.com>; "r-help@r-project.org" <r-help@r-project.org> > Sent: Monday, January 21, 2013 11:10 AM > Subject: RE: [R] dummy encoding in metafor > > As Michael already mentioned, the error: > > Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve > > indeed indicates that your design matrix is not of full rank (i.e., there are > linear dependencies among your predictors). With this many factors in the > same model, this is not surprising if k is "only" 94 (which is actually quite > large for a meta-analysis). One options is to leave out some of the > predictors. You can also try collapsing some of the levels of the factors. Of > course, you lose some "details" that way, but apparently you don't have > enough data in the first place to carry out such a detailed analysis. > > One other thing I noticed. You wrote: > > rma(yi=Mean, vi=Variance, ni=N.1, ...) > > I suspect that your variable "Variance" is actually the variance of the raw > scores. However, the vi argument is used to pass the sampling variances of > the yi values to the function -- not the variance of raw scores. The > (estimated) sampling variance of a mean is s^2 / n, so if I am not mistaken, > you really want to use: > > rma(yi=Mean, vi=Variance/N.1, ...) > > 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: <mailto:r-help-boun...@r-project.org>r-help-boun...@r-project.org > > [mailto:r-help-boun...@r-project.org] > > On Behalf Of Michael Dewey > > Sent: Monday, January 21, 2013 10:40 > > To: Alma Wilflinger; Michael Dewey; > > <mailto:r-help@r-project.org>r-help@r-project.org > > Subject: Re: [R] dummy encoding in metafor > > > > At 14:48 20/01/2013, Alma Wilflinger wrote: > > >Hi, > > > > > >thank you very much for your kind answer. > > > > > > >If you look a bit further down the manual page you will see > > > >### using a model formula to specify the same model > > > >rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method="REML", > > > >btt=c(2,3)) > > > > > > >which is much easier. > > > > > >I have seen the possibility of using a model formula for dummy > > >encoding and you are right it is much easier than doing it by hand. > > >Thing is that if I include some moderator variables into the > > >parameters I get the error: > > > > > >Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve > > > > I suspect that you have a linear dependence between your moderator > > variables. Depending on how many levels there are for country, > > sample, and so on you do have a lot of predictors (you presumably > > know that a factor counts as levels-1 for this purpose?) > > > > > > >For example this call works: > > >result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + > > >relevel(factor(Sample), ref="Students") + Gender + Age + > > >factor(Category) + relevel(factor(Block), ref="c")+ > > >relevel(factor(order), ref="x"), data=csvDataCmaAll, method="REML") > > > > > >If I add the trials which is of type INT: > > >result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + > > >relevel(factor(Sample), ref="Students") + Gender + Age + > > >factor(Category) + relevel(factor(Block), ref="c")+ > > >relevel(factor(order), ref="x") + trials, data=csvDataCmaAll, > > method="REML") > > > > > >I get the error and I was not able to find a definite reason for > > >this error or how to solve it I wanted to try it by doing it manually. > > >I think I have found out that it somehow relates to the > > > > > > >If you code them yourself R does not know. You know. > > > > > >Regarding this I think my question was not clear enough. If R does > > >the dummy encoding automatically via a model formula it leaves out > > >one of the factors and uses it as a baseline automatically. If I do > > >it by hand R is still able to execute the function but the baseline > > >is missing because I do not define it via a parameter. > > > > You perhaps would benefit from rereading some of the introductory > > material about formulas. Also look for anything about the model > > matrix (also called the design matrix) > > > > >I simply want to know how R is handling this and what I have to do > > >by hand to get the correct results. Sorry, this may be a beginners > > >question, but as stated I am new to this field. > > > > > > >You say you have seven moderator variables. Unless you have a shed > > > >load of studies you will not be able to look at them simultaneously. > > > >Apologies if you already knew that. > > > > > >No I have not known that. In total I have about 94 studies and want > > >to test different sets of moderators. Do you think this is > > >sufficient or do you suggest another approach? > > > > The truthful but perhaps unhelpful answer is that you need to collect > > more data or use fewer moderators. > > > > >I started in CMA (comprehensive meta analysis) but one of the > > >benefits of R is that I am able to test multiple moderators at once > > >- at least as I was told. > > > > > >kind regards, > > >Alma > > > > > > > > >From: Michael Dewey > > ><<mailto:i...@aghmed.fsnet.co.uk>i...@aghmed.fsnet.co.uk> >; "<mailto:r-help@r-project.org>r-help@r-project.org" > > ><<mailto:r-help@r-project.org>r-help@r-project.org> > > >Sent: Sunday, January 20, 2013 12:52 PM > > >Subject: Re: [R] dummy encoding in metafor > > > > > >At 17:14 19/01/2013, Alma Wilflinger wrote: > > > >Hi, > > > > > > > >I am quite new to R and in need of some advice. I am trying to > > > >conduct a meta regression over a some studies with about 7 mod > > > >variables which I have to dummy encode. > > > > > >Alma, although you can generate your own dummy variables by hand you > > >do not have to as R will do it for you. See below for more comments. > > > > > > > > > >I have found the following piece of code in the manual for the > > > >metafor library: > > > > > > > >### manual dummy coding of the allocation factor > > > >alloc.random <- ifelse(dat$alloc == "random", 1, 0) > > > >alloc.alternate <- ifelse(dat$alloc == "alternate", 1, 0) > > > >alloc.systematic <- ifelse(dat$alloc == "systematic", 1, 0) > > > > > >If you look a bit further down the manual page you will see > > >### using a model formula to specify the same model > > >rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method="REML", > > >btt=c(2,3)) > > > > > >which is much easier. > > > > > > >### test the allocation factor (in the presence of the other > > moderators) > > > >### note: "alternate" is the reference level of the allocation factor > > > >### note: the intercept is the first coefficient, so btt=c(2,3) > > > >rma(yi, vi, mods=cbind(alloc.random, alloc.systematic, year, ablat), > > > >data=dat, method="REML", btt=c(2,3)) > > > > > > > >What I do not understand is the following: > > > >How does R know which columns in my data.frame are related to the > > > >dummy encoded variables? > > > > > >If you code them yourself R does not know. You know. > > > > > > > > > >It is clear that in the call of cbind I just do not use the > > > >reference variable as a parameter but I do not get it how R knows > > > >that alloc.random and alloc.systematic refer to the column alloc in > > > >the data frame. > > > > > > > >Thank you very much in advance for your help, > > > > > > > > > >You say you have seven moderator variables. Unless you have a shed > > >load of studies you will not be able to look at them simultaneously. > > >Apologies if you already knew that. > > > > > > >kind regards, > > > >Alma > > > > [[alternative HTML version deleted]] > > > > > >Michael Dewey > > ><mailto:i...@aghmed.fsnet.co.uk><mailto:i...@aghmed.fsnet.co.uk>i > > >n...@aghmed.fsnet.co.uk > > >http://www.aghmed.fsnet.co.uk/home.html > > > > > > > > > > Michael Dewey > > <mailto:i...@aghmed.fsnet.co.uk>i...@aghmed.fsnet.co.uk > > http://www.aghmed.fsnet.co.uk/home.html > > > > ______________________________________________ > > <mailto:R-help@r-project.org>R-help@r-project.org mailing list > > <https://stat.ethz.ch/mailman/listinfo/r-help>https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > <http://www.r-project.org/posting->http://www.R-project.org/posting- > > guide.html > > and provide commented, minimal, self-contained, reproducible code. > Michael Dewey i...@aghmed.fsnet.co.uk http://www.aghmed.fsnet.co.uk/home.html [[alternative HTML version deleted]]
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