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 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. 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? 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 <i...@aghmed.fsnet.co.uk> 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 i...@aghmed.fsnet.co.uk http://www.aghmed.fsnet.co.uk/home.html [[alternative HTML version deleted]]
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