[R-meta] [+externe Mail+] Re: forest plot and study-specific effect

[Yefeng Yang]

Dear Christian,

I had a read of your introductive paper about bayesmeta.

A quick question to ask. Under the subsection 2.8. Shrinkage estimates of study-specific means, the formula for computing study-specific effects is presented. I am wondering whether it makes sense to plug-in tau^2_i (tau^2 for each study) rather than the mean/median/mode to the formula, given that each study might not have the same heterogeneity.


All the best,
Yefeng
________________________________
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org> on behalf of R�ver, Christian via R-sig-meta-analysis <r-sig-meta-analysis using r-project.org>
Sent: 06 June 2024 16:25
To: r-sig-meta-analysis using r-project.org <r-sig-meta-analysis using r-project.org>
Cc: R�ver, Christian <christian.roever using med.uni-goettingen.de>
Subject: Re: [R-meta] [+externe Mail+] Re: forest plot and study-specific effect

Dear Yefeng,

the forest plots in the "bayesmeta" package by default show the
shrinkage estimates / BLUPs along with the plain data; see e.g. here:
  https://cran.r-project.org/package=bayesmeta
  https://doi.org/10.18637/jss.v093.i06  (Fig.2)
(bayesmeta's forest plots are based on the "forestplot" package).

I often find this helpful to illustrate the amount of borrowing-of-
information / mutual support between studies, depending on the amount
of heterogeneity. It may in particular also be an interesting option in
cases where the "plain data estimates" may not be readily available,
e.g., when you are looking at a binomial likelihood and some studies
have zero event counts.

Cheers,

Christian


On Wed, 2024-06-05 at 16:54 +0000, Dr. Gerta R�cker via R-sig-meta-
analysis wrote:
> Dear Yefeng,
>
> You may like to have a look at the supplement " traceplot-R-code.R"
> to the paper
> https://onlinelibrary.wiley.com/doi/full/10.1002/jrsm.1693 (R�ver,
> Rindskopf, Friede) that shows how to obtain a joint forest plot with
> study-specific estimates and BLUPs with R package bayesmeta.
>
> Best,
> Gerta
>
>
>
> UNIVERSIT�TSKLINIKUM FREIBURG
> Institute for Medical Biometry and Statistics
>
> Dr. Gerta R�cker
> Guest Scientist
>
> Stefan-Meier-Stra�e 26 � 79104 Freiburg
> gerta.ruecker using uniklinik-freiburg.de
>
> https://www.uniklinik-freiburg.de/imbi-en/employees.html?imbiuser=ruecker
>
> -----Urspr�ngliche Nachricht-----
> Von: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org>
> Im Auftrag von Viechtbauer, Wolfgang (NP) via R-sig-meta-analysis
> Gesendet: Mittwoch, 5. Juni 2024 14:19
> An: R Special Interest Group for Meta-Analysis <
> r-sig-meta-analysis using r-project.org>
> Cc: Viechtbauer, Wolfgang (NP) <
> wolfgang.viechtbauer using maastrichtuniversity.nl>
> Betreff: Re: [R-meta] forest plot and study-specific effect
>
> Dear Yefeng,
>
> Plotting the BLUPs has been done before. See Figure 3 in:
>
> van Houwelingen, H. C., Arends, L. R., & Stijnen, T. (2002). Advanced
> methods in meta-analysis: Multivariate approach and meta-regression.
> Statistics in Medicine, 21(4), 589-624.
>
> Actually, the forest plot shows the individual estimates, plus the
> BLUPs.
>
> You can find a recreation of this here:
>
> https://www.metafor-project.org/doku.php/analyses:vanhouwelingen2002
>
> I think there are various reasons why the default is not to show the
> BLUPs. For example, the estimates are simply what was found in each
> of the invididual studies, while the BLUPs depend on what other
> studies are included in the analysis and the values also depend on
> the specifics of the modeling approach used. But showing both (as
> above) is definitely interesting.
>
> Best,
> Wolfgang
>
> > -----Original Message-----
> > From: R-sig-meta-analysis <
> > r-sig-meta-analysis-bounces using r-project.org> On Behalf
> > Of Yefeng Yang via R-sig-meta-analysis
> > Sent: Wednesday, June 5, 2024 08:14
> > To: r-sig-meta-analysis using r-project.org
> > Cc: Yefeng Yang <yefeng.yang1 using unsw.edu.au>
> > Subject: [R-meta] forest plot and study-specific effect
> >
> > Dear community,
> >
> > I have a small question about the forest plot used in the meta-
> > analysis.
> >
> > The forest plots and their varieties are often used in meta-
> > analysis papers to
> > show the overall/grand mean, individual effect size estimates, and
> > other
> > relevant info depending on the software making them. We know the
> > effect size
> > estimates from individual studies are usually noisy or not very
> > precise. But,
> > why do meta-analysts prefer to report individual effect size
> > estimates rather
> > than the study-specific effects (which benefit from the shrinkage
> > or borrowing
> > of strength). Or, put differently, the developers of software that
> > can make
> > forest plots do not seem to provide the option of showing study-
> > specific effects
> > (I did not check carefully; some software or packages might provide
> > this
> > functionality). Is there any specific reason? Or, it is just a
> > convention.
> >
> > Best,
> > Yefeng
>
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