[R-meta] best subset of moderators for `robumeta` package in R

Reza Norouzian rnorouz|@n @end|ng |rom gm@||@com
Thu Nov 7 19:24:47 CET 2019

Thank you, what I'm after is to possibly get the best subsets for `robu()`
which unfortunately doesn't provide *logLik *or *AIC *to get it connected
to the packages you suggested. Using `*robust()*` in metafor for large
number of studies unfortunately doesn't change results compared to its `
*rma()*` counterpart, also the results are all significantly different from

My concern is that running best subset analysis using metafor may not
translate into finding the best model for `*robu()*`. As a result, I wonder
if there might be a way to either obtain AIC etc. from `robu()` to connect
it to the packages you mentioned OR to make the packages you mentioned take
"I2" as criteria not AIC etc.?

Thanks very much,

On Thu, Nov 7, 2019 at 12:12 PM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> I am not entirely sure what you are after with using I^2 in this context,
> but using the same example, this is how you would find the model with the
> lowest I^2 value:
> I2s <- sapply(res using objects, function(x) x$I2)
> res using objects[which.min(I2s)]
> Best,
> Wolfgang
> -----Original Message-----
> From: Reza Norouzian [mailto:rnorouzian using gmail.com]
> Sent: Thursday, 07 November, 2019 18:42
> To: Viechtbauer, Wolfgang (SP)
> Cc: R meta
> Subject: Re: [R-meta] best subset of moderators for `robumeta` package in R
> Dear Wolfgang,
> Thank you so much for this truly awe-inspiring response (I really can't
> stop reading your post) !! At the cost of being ignorant, is there any way
> to focus on "I2" index instead of information-theoretic criteria in these
> model-finding quests using the packages you mentioned?
> Once again, I truly appreciate your expertise and time on this,
> Reza
> On Thu, Nov 7, 2019 at 5:44 AM Viechtbauer, Wolfgang (SP) <
> wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> Hi Reza,
> I haven't played around with the leaps package, but you could do this with
> glmulti or MuMIn. An example of how to do this in combination with metafor
> is given here:
> http://www.metafor-project.org/doku.php/tips:model_selection_with_glmulti_and_mumin
> One could add additional steps to the rma.glmulti() function shown there,
> such as robust() from metafor or using coef_test() from clubSandwich.
> But note that with 35 moderators, you are looking at 2^35 = 34,359,738,368
> possible models. Even if fitting a single model only takes 0.01 seconds
> (which is rather optimistic), you will wait about 11 years for this to
> finish. If you have a cluster and parallelize this, you might be able to
> get this down to weeks or months. But one could also wonder if this is a
> useful exercise in the first place.
> You could restrict your search to models with at most 'm' predictors. For
> m = 8, that's choose(35,8) = 23,535,820 models, which is still a lot but
> more feasible. glmulti() has a 'maxsize' argument for this purpose.
> dredge() from MuMIn has argument 'm.lim' for this.
> Best,
> Wolfgang
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Reza Norouzian
> Sent: Thursday, 07 November, 2019 3:24
> To: R meta
> Subject: [R-meta] best subset of moderators for `robumeta` package in R
> I have a large number of "categorical" moderators (35 moderators). I am
> planning to use the best subset of these moderators that can maximally
> explain the variation in my 257 correlated effect sizes from 51 studies.
> The R package `*leaps*` does perform best possible subset analysis via
> function `*regsubsets()*` but to make that suited to `*robu()*` I think
> need to define `weights` argument in `*regsubsets()*` so I can basically
> make this suited for RVE purposes not simply OLS regression.
> Any idea regarding how I can execute my plan in R or generally how I can
> choose best subset of moderators for `*robu()*` in `robumeta` in R?
> Many thanks,
> Reza
> --
> *Reza Norouzian*

*Reza Norouzian*
Postdoctoral Research Associate | Lecturer
Second Language Acquisition & Research Methods, Ph.D.
College of Education & Human Development
Dep. of Teaching, Learning & Culture | Texas A&M University
College Station, TX 77843
Webpage: *https://directory.education.tamu.edu/view.epl?nid=rnorouzian
Email: rnorouzian using tamu.edu
Phone: (979)-422-7052
*Future L2 researchers will be challenged not only on the basis of their
substantive questions, but also on how they manage to answer those
questions in a methodical manner.*

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