Hello again everyone,
I tired to use the arguments that you suggested Gerta, (col.study, col.square, col.square.lines and col.inside),but every time I got the same result, with nothing changed from the original plot,and warnings that read " In segments(...) : "col.study" is not a graphical parameter ".I tried to run the example you gave me though, and it worked alright, even though there were many lines not fitting in the plot I believe, but I could see the different colours for each effect size or for groups of effect sizes.Also, I am working with an object that is the result of using the rma function from the package metafor, and I don't quite understand what difference exists between rma, meta, and robu objects.I used the robu() function to have a result that accounts for the fact that some of the studies I use provide multiple effect-sizes to my meta-analysis, as shown in the youtube video by Daniel Quintana explaining his 2015 article,"From pre-registration to publication : a non-technical primer for conducting a meta-analysis to synthesize correlational data".However, when I try to use the forest function with the robu object it doesn't work.Would you know what exactly differs between these rma, meta, and robu objects ? I understand that they are the results of different functions, but they are supposed to be meta-analysis results, so in my mind they should have been of the same format, or at least I should still be able to use the robu object in the forest function since the forest plot is the main result of the meta-analysis.
Do you have any advice ?Thank you !Norman
----- Mail d'origine -----
De: Norman DAURELLE <norman.daurelle at agroparistech.fr>
?: r-sig-meta-analysis at r-project.org
Cc: Michael Dewey <lists at dewey.myzen.co.uk>, ruecker at imbi.uni-freiburg.de
Envoy?: Thu, 04 Jun 2020 01:12:06 +0200 (CEST)
Objet: Re: [R-meta] adapting forest plot visual
Dear all, dear Greta and Michael,
thank you for your answers, I am indeed using the function forest (or forest.rma, which gives the same result I think when I look up the documentation through "help") from the package meta.
I use the rma() function from the metafor package to perform the meta-analysis. I have read about the forestplot function from the package named the same, and I tried to use it, but the first plot I got with it was not that nice, so I went back to digging deeper into the forest function from the package meta.
Special thanks Greta for the advice about the arguments col.study, col.square, col.square.lines and col.inside, I was trying to use the argument leftcols, without much success.
Have a nice day !
Norman
----- Mail d'origine -----
De: Gerta Ruecker <ruecker at imbi.uni-freiburg.de>
?: Michael Dewey <lists at dewey.myzen.co.uk>, Norman DAURELLE <norman.daurelle at agroparistech.fr>, r-sig-meta-analysis at r-project.org
Envoy?: Wed, 03 Jun 2020 11:22:15 +0200 (CEST)
Objet: Re: [R-meta] adapting forest plot visual
I think he mentioned the meta package, therefore I provided an example
how to do it in meta. Disclaimer: I have often used it myself ;-)
Best,
Gerta
Am 03.06.2020 um 11:05 schrieb Michael Dewey:
Dear Norman
There is a package on CRAN called forestplot which claims to provide
comprehensive options for controlling the forest plot so if you cannot
find how to do it in your preferred package (which you do not name
incidentally) then it might be worth investigating. Disclaimer: I have
never used it myself.
Michael
On 02/06/2020 12:24, Norman DAURELLE wrote:
Dear list,I have now run a meta-analysis based on relationship slopes
between two variables and I am trying to make the forest plot easily
readable and understandable.I used the "order" parameter of the
forest function to order outcomes from lowest estimate on the first
line to highest estimate on the last line, but I would like to
display the outcomes that share a characteristic in the same colour (
for example, all effect-sizes coming from studies conducted in the
same country displayed in one colour ). I have been looking for a way
to do that in the documentation of the forest function of the meta
package, but there are a lot of arguments to that function and I
can't find one that does what I would like to do. It doesn't
necessarily have to be based on colour but if I can change the shape
of the square representing the effect sizes that come from the same
place for example that would also do the trick, even though colour is
more direct.Would you know of a way to do that ? Thank
--
Dr. rer. nat. Gerta R?cker, Dipl.-Math.
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg
Stefan-Meier-Str. 26, D-79104 Freiburg, Germany
Phone: +49/761/203-6673
Fax: +49/761/203-6680
Mail: ruecker at imbi.uni-freiburg.de
Homepage: https://www.uniklinik-freiburg.de/imbi.html