[R-meta] Questions about Omnibus tests

[Rafael Rios]

Thanks a lot, Wolfgang!

Best wishes,

Rafael.
__________________________________________________________

Dr. Rafael Rios Moura
*scientia amabilis*

Behavioral Ecologist, PhD
Postdoctoral Researcher
Universidade Estadual de Campinas (UNICAMP)
Campinas, São Paulo, Brazil

Currículo Lattes: http://lattes.cnpq.br/4264357546465157
ORCID: http://orcid.org/0000-0002-7911-4734
Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2




<http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4244908A8>


Em qui, 8 de nov de 2018 às 15:07, Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:

> I don't think there is an inherent need to 'handle high heterogeneity'.
> The data might be highly heterogeneous, but that might just be a reflection
> of the nature of the phenomenon under investigation.
>
> On the other hand, there might be outliers and/or highly influential
> studies and I think it is useful to try to identify them. rstandard() and
> cooks.distance() are useful for this. Then one can present results with and
> without those studies to see how much this impacts the results. It seems
> like you have done that already.
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: Rafael Rios [mailto:biorafaelrm using gmail.com]
> Sent: Thursday, 08 November, 2018 17:50
> To: Viechtbauer, Wolfgang (SP)
> Cc: r-sig-meta-analysis using r-project.org
> Subject: Re: [R-meta] Questions about Omnibus tests
>
> Dear Wolfgang,
>
> Thank you for the clarification! There are just a few more questions that
> I hope you may help me.
>
> I used your script to calculate I² and found a high heterogeneity in my
> model (86.63%).
> #I²:
> http://www.metafor-project.org/doku.php/tips:i2_multilevel_multivariate
> W <- diag(1/h_mc$vzf)
> X <- model.matrix(model1)
> P <- W - W %*% X %*% solve(t(X) %*% W %*% X) %*% t(X) %*% W
> 100 * sum(meta$sigma2) / (sum(meta$sigma2) + (meta$k-meta$p)/sum(diag(P)))
>
> Do you have suggestions on how to handle with high heterogeneity among
> effect sizes? How may I conduct sensitivity tests in a multilevel
> meta-analysis using metafor? I identified (using a funnel plot) and removed
> outliers to reduce the heterogeneity and redo the model. Then, I compared
> the results of both models to evaluate if there is any discrepancies. Is
> this approach suitable to evaluate potential bias in the results? Or are
> there better alternatives?
>
> Best wishes,
>
> Rafael.
> __________________________________________________________
>
> Dr. Rafael Rios Moura
> scientia amabilis
>
> Behavioral Ecologist, PhD
> Postdoctoral Researcher
> Universidade Estadual de Campinas (UNICAMP)
> Campinas, São Paulo, Brazil
>
> Currículo Lattes: http://lattes.cnpq.br/4264357546465157
> ORCID: http://orcid.org/0000-0002-7911-4734
> Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
>
> Em qui, 8 de nov de 2018 às 13:48, Viechtbauer, Wolfgang (SP) <
> wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:
> As for the model to use:
>
> In general, you want to use: ~1|studyID/effectsizeID
>
> Using list(~1|effectsizeID, ~1|studyID) may be correct if effectsizeID is
> unique for every row.
>
> This is essentially a question of 'explicit' versus 'implict' nesting. See
> also:
>
> https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2018-July/000896.html
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: Rafael Rios [mailto:biorafaelrm using gmail.com]
> Sent: Sunday, 04 November, 2018 0:32
> To: Viechtbauer, Wolfgang (SP)
> Cc: Michael Dewey; r-sig-meta-analysis using r-project.org
> Subject: Re: [R-meta] Questions about Omnibus tests
>
> Dear Wolfgang,
>
> Could you please help me again with new questions?
>
> Should I build model1 rather than model2 to control for the dependency
> among studyID and effectsizeID?
>
> model1=rma.mv(zf, vzf, mods=~mate_choice,
> random=list(~1|studyID/effectsizeID, ~1|species1), data = h_mc)
> model2=rma.mv(zf, vzf, mods=~mate_choice, random=list(~1|effectsizeID,
> ~1|studyID, ~1|species1), data = h_mc)
>
> I used your script to calculate I² and found a high heterogeneity in my
> model (86.63%).
> #I²:
> http://www.metafor-project.org/doku.php/tips:i2_multilevel_multivariate
> W <- diag(1/h_mc$vzf)
> X <- model.matrix(model1)
> P <- W - W %*% X %*% solve(t(X) %*% W %*% X) %*% t(X) %*% W
> 100 * sum(meta$sigma2) / (sum(meta$sigma2) + (meta$k-meta$p)/sum(diag(P)))
>
> Do you have suggestions on how to handle with high heterogeneity among
> effect sizes? How may I conduct sensitivity tests in a multilevel
> meta-analysis using metafor? I identified (using a funnel plot) and removed
> outliers to reduce the heterogeneity and redo the model. Is this approach
> suitable to evaluate potential bias in results? Or are there better
> alternatives?
>
> Best wishes,
>
> Rafael.
> __________________________________________________________
>
> Dr. Rafael Rios Moura
> scientia amabilis
>
> Behavioral Ecologist, PhD
> Postdoctoral Researcher
> Universidade Estadual de Campinas (UNICAMP)
> Campinas, São Paulo, Brazil
>
> Currículo Lattes: http://lattes.cnpq.br/4264357546465157
> ORCID: http://orcid.org/0000-0002-7911-4734
> Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
>

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