[R-meta] fixed-effect multivariate model interpretation

[Filippo Gambarota]

Thank you! the chapter and the link are extremely helpful!

On Mon, 3 Jan 2022 at 19:46, Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> See for example the Gleser & Olkin chapter:
>
> Gleser, L. J., & Olkin, I. (2009). Stochastically dependent effect sizes.
> In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of
> research synthesis and meta-analysis (2nd ed., pp. 357–376). New York:
> Russell Sage Foundation.
>
> https://www.metafor-project.org/doku.php/analyses:gleser2009
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: Filippo Gambarota [mailto:filippo.gambarota using gmail.com]
> >Sent: Monday, 03 January, 2022 18:02
> >To: Viechtbauer, Wolfgang (SP)
> >Cc: R meta
> >Subject: Re: [R-meta] fixed-effect multivariate model interpretation
> >
> >Ah great! do you have any references for this? because I would like to
> clearly
> >understand what is going on. Cochrane's Q-statistic is the deviation of
> each
> >study from the estimated average effect weighted by the precision. In
> this case,
> >the "average" effect is the average between outcomes? Or the formula is
> >different?
> >Thank you!
> >
> >On Mon, 3 Jan 2022 at 17:12, Viechtbauer, Wolfgang (SP)
> ><wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> >It's just the multivariate version of Cochrane's Q-test. It does not
> estimate a
> >random-effects model. It simply tests whether the observed amount of
> variability
> >is larger than expected based on the sampling variances (and their
> covariances
> >when V includes those) and any moderators specified.
> >
> >Best,
> >Wolfgang
> >
> >>-----Original Message-----
> >>From: Filippo Gambarota [mailto:filippo.gambarota using gmail.com]
> >>Sent: Monday, 03 January, 2022 17:11
> >>To: Viechtbauer, Wolfgang (SP)
> >>Cc: R meta
> >>Subject: Re: [R-meta] fixed-effect multivariate model interpretation
> >>
> >>Thank you Wolfgang!
> >>So my related question is how this residual heterogeneity is estimated
> in order
> >>to compute the Q statistic? Because if the model is still estimating and
> testing
> >>the presence of heterogeneity, from a multivariate model I would have
> expected
> >>one residual heterogeneity term for each outcome (the same as I have one
> tau per
> >>outcome if I fit the random-effect version).
> >>
> >>On Mon, 3 Jan 2022 at 16:50, Viechtbauer, Wolfgang (SP)
> >><wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> >>Hi Filippo,
> >>
> >>You can *assume* that there is no residual heterogeneity, but there may
> be. That
> >>is what the test of residual heterogeneity is testing here (whether your
> >>assumption is correct or not).
> >>
> >>Best,
> >>Wolfgang
> >>
> >>>-----Original Message-----
> >>>From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org] On
> >>>Behalf Of Filippo Gambarota
> >>>Sent: Monday, 03 January, 2022 16:42
> >>>To: R meta
> >>>Subject: [R-meta] fixed-effect multivariate model interpretation
> >>>
> >>>Hello!
> >>>I'm fitting for the first time a multivariate fixed-effect model using
> >>>metafor. The code is:
> >>>
> >>>```
> >>>rma.mv(yi, V, mods = ~ 0 + outcome, data = data, test = "t")
> >>>```
> >>>Where V is the block variance-covariance matrix created with vcalc()
> >>>that represents the covariance between different outcome levels within
> >>>each study. The outcome is a factor that represents different effect
> >>>sizes measured on the same participants within a study.
> >>>The model as expected did not estimate tau for each outcome and test
> >>>all coefficients (each outcome mean with this parametrization) against
> >>>0 (both the omnibus test and each beta). My question is about the
> >>>*residual heterogeneity* parameter and the associated Q test. Under
> >>>this model, I should have assumed that there is no heterogeneity
> >>>within each outcome level so I'm not sure how to interpret the
> >>>residual heterogeneity in this case.
> >>>Thank you!
> >>>Filippo
> >>>
> >>>--
> >>>Filippo Gambarota
> >>>PhD Student - University of Padova
> >>>Department of Developmental and Social Psychology
> >>>Website: filippogambarota.netlify.app
> >>>Research Group: Colab   Psicostat
>


-- 
*Filippo Gambarota*
PhD Student - University of Padova
Department of Developmental and Social Psychology
Website: filippogambarota.netlify.app
Research Group: Colab <http://colab.psy.unipd.it/>   Psicostat
<https://psicostat.dpss.psy.unipd.it/>

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