[R-meta] Nestedness in meta-analysis data using R (metafor or metaSEM packages)

[Reza Norouzian]

Thanks, James, very useful. If I may, the adjustment for small samples in
correlated models using `robumeta` package corrects for the small number of
effect sizes within each cluster, or the small number of clusters (i.e.,
studies) themselves, or both?

Thanks, Reza

On Mon, Nov 4, 2019 at 9:39 PM James Pustejovsky <jepusto using gmail.com> wrote:

> Reza,
>
> Here is a recent article provides a review of the main analytic approaches
> available for the data structure that you've described:
>
>    - Moeyaert, M., Ugille, M., Natasha Beretvas, S., Ferron, J., Bunuan,
>    R., & Van den Noortgate, W. (2017). Methods for dealing with multiple
>    outcomes in meta-analysis: a comparison between averaging effect sizes,
>    robust variance estimation and multilevel meta-analysis. *International
>    Journal of Social Research Methodology*, *20*(6), 559-572.
>
> The question has come up periodically on the mailing list too, so you
> might find past posts helpful. A few to get you started:
>
>    -
>    https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2017-September/000197.html
>
>    -
>    https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2017-August/000094.html
>
>    -
>    https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2019-March/001479.html
>
>    -
>    https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2018-October/001153.html
>
>
> James
>
> On Sun, Nov 3, 2019 at 7:36 PM Reza Norouzian <rnorouzian using gmail.com>
> wrote:
>
>> Hi,
>>
>> I have 51 studies. These studies have produced 257 effect sizes (denoted
>> y).
>> In each study, each effect size is obtained some time (categorized as 1,
>> 2,
>> 3, 4) after a treatment. Also, in15 of the studies, some effect sizes have
>> been reported on up to 4 correlated outcomes.
>>
>> What reasonable model using the library(metafor) [e.g., via rma.mv] or
>> library(metaSEM) [e.g., via meta3] can capture the structure of my data
>> described above?
>>
>> For concreteness, I'm providing demo data below.
>>
>> d <- read.csv("https://raw.githubusercontent.com/izeh/m/master/e.csv",
>> h = T) # DATA
>> # First 6 lines of DATA:
>>
>>           study.name            y        SD id outcome time 1
>> Al.Ahm_Al.Jar  0.533733731 0.4286817  1       1    1          2
>> Al.Ahm_Al.Jar  0.296116599 0.4132781  1       1    4          3
>> Al.Ahm_Al.Jar -0.155386371 0.4267881  1       1    1          4
>> Al.Ahm_Al.Jar  0.131015334 0.4384274  1       1    4          5
>>     Al_Ajmi  3.444226818 0.2182068  2       1    1          6
>>   Al_Ajmi  4.376457433 0.2090771  2       1    2
>>
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>>
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>>
>

-- 
*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
<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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