[R-meta] Subgroup analyses under the multi-level (3 level) meta-analysis model

-----Original Message-----
From: Saya Fujita [mailto:sayakaf.p at gmail.com]
Sent: Sunday, 14 March, 2021 17:43
To: Viechtbauer, Wolfgang (SP)
Subject: Re: Subgroup analyses under the multi-level (3 level) meta-analysis model

Dear Professor Viechtbauer,

Thank you very much for your prompt response!

I ran the code using my original variables "Metrics" as factors.
I can see it has 4 levels, but my regression results only show 3 factors.
I am wondering why?

The Metrics has 4 levels (Coupling, Flow, Graph, Corr) as seen below:

str(multi.data$Metrics)

Factor w/ 4 levels "Corr","Coupling",..: 1 1 1 1 1 1 1 1 1 1 ...

Here's my codes:

subEEG.Metrics<-rma.mv(y,
                  v,
                  random = ~ 1 | PaperID/AnalysisID,
                  tdist = TRUE,
                  data = multi.data,
                  method = "REML",
                  mods = ~ Metrics)

And the results are:

Model Results:

                estimate      se     tval    pval    ci.lb   ci.ub
intrcpt            0.8795  0.2458   3.5788  0.0005   0.3933  1.3658  ***
MetricsCoupling   -0.1432  0.2982  -0.4804  0.6318  -0.7332  0.4468
MetricsFlow        0.1238  0.4307   0.2876  0.7742  -0.7283  0.9760
MetricsGraph      -0.0084  0.4257  -0.0196  0.9844  -0.8506  0.8339

If you could kindly let me know whether I am doing something wrong, I would be so
appretiative!

Thank you very much again!

Warmest regards,
Saya

?On 14/03/2021, 15:52, "Viechtbauer, Wolfgang (SP)"
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

   Dear Saya,

   You do not need to create these 'dummy variables' yourself. Just declare the
variable that distinguishes the various subgroups as a factor and include it as a
predictor via 'mods'. You also might want to read this:

   https://www.metafor-project.org/doku.php/tips:models_with_or_without_intercept

   It's not focused on rma.mv() (i.e., it uses a simpler model), but the same
principles apply.

   Best,
   Wolfgang

   >-----Original Message-----
   >From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org]

On

   >Behalf Of Saya Fujita
   >Sent: Sunday, 14 March, 2021 16:24
   >To: R-sig-meta-analysis at r-project.org
   >Subject: [R-meta] Subgroup analyses under the multi-level (3 level) meta-

analysis

   >model
   >
   >Dear All,
   >
   >I am conducting a 3-level multi-analysis, following this Bookdown.
   >https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/mlma.html
   >
   >I would like to run some sub-group analyses under this 3 level structure, and

I

   >can see in this bookdown (chapter 12.1) that if I use rma.mv function in

metafor,

   >we need to create two variables/columns for each subgroup level. In the

example in

   >this book down, the number of sub-groups was two: peer-review, dissertation,

so it

   >makes sense that they coded 1 (yes) or 0 (no).
   >
   >In my data I have more than two subgroups, and I wonder how I should input

the

   >data. I thought, if I have 4 subgroups for instance, I?d create 4 columns and

code

   >0 or 1 in each column, but that would group 3 different levels as 0 in one

column,

   >and specifying one variable/column as a moderator in rma.mv using
   >the mods parameter would compare one subgroup with the other three subgroups

?

   >which is not what I want to do. Hope this makes sense!
   >I wonder if anyone here has done a subgroup analysis for multiple subgroup
   >comparisons, maintaining the 3 level structure of a multi-level meta-

analysis?

   >Could I ask how you did the analysis?
   >
   >Thank you very much in advance, and I apologise if it?s a very simple/na?ve
   >question!
   >
   >Many thanks,
   >Saya
   >
   >*********
   >Sayaka Kidby (Fujita)| PhD candidate, Marie Sk?odowska-Curie Early Career
   >Researcher [she/her]
   >Psychology | Lancaster University
   >s.kidby at lancaster.ac.uk
   >www.lancaster.ac.uk