[R-sig-ME] weights in mixed modelling

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Thu Jan 14 19:22:07 CET 2021

Hi Alex,

The analysis that you're working on sounds like what would be called an
"individual participant data meta-analysis." You might find the literature
on that topic helpful in thinking about analytic approaches.

In the meta-analysis literature, there's been quite a bit of discussion
about the idea of using weighting as a means to address issues of variable
study quality. My sense of it is that the consensus in the meta-analysis
context is that weighting by study quality is not recommended. Two papers
to give you a flavor of the discussion:

An alternative to using study-quality weights would be to use the study
quality index (or perhaps the sub-components of the index) as predictors in
your analysis. This would allow you to, for example, make predictions about
whatever the target quantity of interest would be in a (hypothetical) study
that had a perfect quality index.

Kind Regards,

On Thu, Jan 14, 2021 at 11:03 AM Baecher,Joseph Alex <jbaecher using ufl.edu>

> Hi everyone,
> I’m looking for advice and/or information about using weights in mixed
> modelling. My colleagues and I are conducting an analysis and we’ve
> attempted to use weights to solve two issues. As is likely obvious, I am
> not a statistician, so please excuse my ignorance! We’re using data
> gathered from several hundred studies. The studies represent a spectrum of
> quality and robustness and therefore we have created an standardized “index
> of study quality” to rank each of the data sources. It was our (perhaps
> dubious) understanding that we could use such an index as model weights in
> our analysis. There are also instances in which studies’ presented data in
> aggregate, and therefore we had to break data into multiple observations.
> We had hoped weights could mitigate any issues arising from
> pseudoreplication. For this, we created an “observation weight”, in which
> each independent observation was assigned a weight of 1 and observations
> which were broken into multiple observations were given a weight = 1/(# of
> observations). We thought combining the “index of study qualities” with the
> “observation weight” via multiplication could give us a composite weight…
> The model we are using is a Beta-distributed mixed effects model, fitted
> using  ‘glmmTMB’.
> If you have any advice or suggestions or relevant reading materials, I
> would greatly appreciate it.
> Thank you in advance for your time and patience,
> All the Best,
> -Alex B.
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~
> J. Alex Baecher (he, him, his)
> PhD student, Research Assistant
> School of Natural Resources and Environment
> University of Florida
> 354 Newins-Ziegler Hall
> Gainesville, Florida 34611 (USA)
> --
> phone: ‪(352) 575-0454
> e-mail: jbaecher using ufl.edu<mailto:jbaecher using ufl.edu>
> website: www.alexbaecher.com<http://www.alexbaecher.com/>
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~
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