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

[Dylan Johnson]

Unfortunately the error persists even after making your correction







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: Viechtbauer, Wolfgang (SP)<mailto:wolfgang.viechtbauer using maastrichtuniversity.nl>
Sent: December 9, 2020 1:56 PM
To: Dylan Johnson<mailto:dylanr.johnson using mail.utoronto.ca>
Cc: R meta<mailto:r-sig-meta-analysis using r-project.org>
Subject: RE: [R-meta] Egger's test with multilevel meta analysis



EXTERNAL EMAIL:

That call to rma.mv() doesn't look right. Maybe you meant:

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

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org]
>On Behalf Of Dylan Johnson
>Sent: Wednesday, 09 December, 2020 19:37
>To: James Pustejovsky; Tobias Saueressig
>Cc: R meta
>Subject: Re: [R-meta] Egger's test with multilevel meta analysis
>
>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
>
>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:
>* Fern�ndez-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

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