[R] metafor

Michael Dewey
Mon, 07 May 2012 08:39:48 -0000

At 18:03 05/05/2012, Jin Choi wrote:
>Dear users of metafor,
>
>I am working on a meta-analysis using the metafor package. I have a
>excel csv database that I am working with. I am interested in pooling
>the effect measures for a particular subgroup (European women) in this
>csv database. I am conducting both sub-group and meta-regression.
>
>In subgroup-analyses, I have stratified the database to create a
>separate csv file just for European women from the original database
>and conducted the following:

Dear Jin
There is a third option, using the original dataset and the subset
parameter to metafor. What happens if you do that? It would rule out
any possibility that your women_west dataset is not in fact the same
as the data on European women in the adult dataset.


>women_west<-read.csv("women_west.csv")
>print(women_west)
>dat<-escalc(measure="ZCOR",ri=Pearson,ni=N,data=women_west,append=TRUE)
>res<-rma(yi,vi,data=dat)
>is.factor(dat$year)
>forest(res,transf=transf.ztor)
>
>In meta-regression, I used the original database, but used categorical
>moderators for sex (=women), and ethnicity (=european) to find the
>effect specifically in European women.
>adult<-read.csv("adult.csv")
>print(adult)
>dat<-escalc(measure="ZCOR",ri=Pearson,ni=N,data=adult,append=TRUE)
>res<-rma(yi,vi,data=dat)
>res<-rma(yi,vi,mods=cbind(sex,race),data=dat)
>predict(res,transf=transf.ztor,newmods=cbind(seq(from=0,to=1,by=1),1),addx=TRUE)
>
>I am getting different results between the forest function from
>subgroup analyses, and the predict function from the meta-regression.
>I thought they should have been the same - can I get help to explain
>why there are differences? In both cases, I am transforming raw
>Pearson coefficients to z-transformed coefficients, then
>back-transforming to raw r after pooling.
>
>Thank you very much.
>
>Jin Choi
>MSc (Epidemiology) Student
>McGill University, Montreal CANADA

Michael Dewey
info at aghmed.fsnet.co.uk