[R-meta] Egger's test with multilevel meta analysis

[Dylan Johnson]

I have tried the following:

egger_multi <- rma.mv(HEDGE_G, HEDGE_VAR, random = ~ 1 | COHORT_ID, EFFECT_ID, mods = ~ STD_ERR, data = dataset)

coeftest(egger_multi, vcov = "CR2")

When I run the coeftest I receive the error:

Error in diag(se) : invalid 'nrow' value (too large or NA)
In addition: Warning message:
In diag(se) : NAs introduced by coercion



Dylan Johnson, MSc

MA Student, School and Clinical Child Psychology
Department of Applied Psychology and Human Development

University of Toronto
252 Bloor Street West

Toronto, ON M5S 1V6

From: James Pustejovsky<mailto:jepusto using gmail.com>
Sent: December 9, 2020 1:20 PM
To: Tobias Saueressig<mailto:t.saueressig using gmx.de>
Cc: Dylan Johnson<mailto:dylanr.johnson using mail.utoronto.ca>; R meta<mailto:r-sig-meta-analysis using r-project.org>
Subject: Re: [R-meta] Egger's test with multilevel meta analysis

EXTERNAL EMAIL:
We have a paper (forthcoming in Psych Methods) evaluating a similar method for adapting Egger's test to the multilevel context, using RVE:
* Rodgers, M. A., & Pustejovsky, J. E. (In Press). Evaluating Meta-Analytic Methods to Detect Selective Reporting in the Presence of Dependent Effect Sizes. Psychological Methods, forthcoming. https://doi.org/10.31222/osf.io/vqp8u

There is also a related paper by Fernandez-Castilla and colleagues:
* Fernández-Castilla, B., Declercq, L., Jamshidi, L., Beretvas, S. N., Onghena, P., & Van den Noortgate, W. (2019). Detecting selection bias in meta-analyses with multipleoutcomes: A simulation study. The Journal of Experimental Education, 1–20.

These tests can be implemented in rma.mv<http://rma.mv>() simply by including the standard error of the effect size (or a related measure of precision, such as the sample size) as a moderator. Say that data includes a variable called sei for the standard error of each effect size:

egger_multi <- rma.mv<http://rma.mv>(yi = yi, V = sei^2, random = ~ 1 | studyID, effectID, mods = ~ sei, data = dat)

Then apply cluster-robust standard errors for the RVE-based test:

coef_test(egger_multi, vcov = "CR2")

Further details available in our paper, and example code in our supplementary materials.

James

On Wed, Dec 9, 2020 at 12:07 PM <t.saueressig using gmx.de<mailto:t.saueressig using gmx.de>> wrote:
Hi Dylan,

you might want to look at this https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13342

And this

https://cran.r-project.org/web/packages/xmeta/

Regards

Tobias



Am 09.12.2020 18:54 schrieb Dylan Johnson <dylanr.johnson using mail.utoronto.ca<mailto:dylanr.johnson using mail.utoronto.ca>>:

Hello,

I am in the process of carrying out a multilevel meta analysis using �rma.mv<http://rma.mv>�. Unfortunately, it does not seem like this type of model can be used with the dmetar �eggers.test� function.

Does anyone have any suggestions for how I could get around this?

Many thanks!

Dylan



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