[R-meta] robust variance estimation with few clusters
Filippo Gambarota
||||ppo@g@mb@rot@ @end|ng |rom gm@||@com
Thu Jul 25 18:16:24 CEST 2024
thank you James, I guess that the same reasoning could be applied to
meta-regression right? I can just ignore the dependency and then apply the
cluster robust function
On Thu, 25 Jul 2024 at 16:42, James Pustejovsky <jepusto using gmail.com> wrote:
> Hi Filippo,
>
> Your approach is to fit a univariate model and then cluster the standard
> errors to allow for dependence across effects nested within papers. RVE is
> based on using working models for the dependence structure, and so we might
> call this approach an "independent effects" working model. Your approach
> seems totally reasonable to me, especially if the higher-level structure is
> difficult to estimate (because of few effects per cluster).
>
> James
>
> On Thu, Jul 25, 2024 at 8:08 AM Filippo Gambarota via R-sig-meta-analysis <
> r-sig-meta-analysis using r-project.org> wrote:
>
>> Hi,
>> I'm approaching the robust variance estimation using clubsandwhich and
>> following the metafor documentation, however I'm not sure about a point. I
>> have a dataset with a multilevel structure (independent effects within a
>> paper). However the number of clusters is low as well as the number of
>> effects within clusters.
>>
>> My idea was to fit a standard two-level model ignoring the multilevel
>> structure (author/id is the paper/effect structure):
>>
>> ```
>> fit <- rma(yi, vi, data = data)
>> robust(fit, cluster = author, clubSandwich = TRUE)
>> ```
>> However in the metafor documentation the robust function is used on a
>> multilevel model. Do I have to fit a multilevel model (with the problem of
>> having few clusters) and then the robust function or my approach is
>> correct?
>>
>> thank you
>>
>> --
>> *Filippo Gambarota, PhD*
>> Postdoctoral Researcher - University of Padova
>> Department of Developmental and Social Psychology
>> Website: filippogambarota.xyz
>> Research Groups: Colab <http://colab.psy.unipd.it/> Psicostat
>> <https://psicostat.dpss.psy.unipd.it/>
>>
>> [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-meta-analysis mailing list @ R-sig-meta-analysis using r-project.org
>> To manage your subscription to this mailing list, go to:
>> https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
>>
>
--
*Filippo Gambarota, PhD*
Postdoctoral Researcher - University of Padova
Department of Developmental and Social Psychology
Website: filippogambarota.xyz
Research Groups: Colab <http://colab.psy.unipd.it/> Psicostat
<https://psicostat.dpss.psy.unipd.it/>
[[alternative HTML version deleted]]
More information about the R-sig-meta-analysis
mailing list