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

[Viechtbauer, Wolfgang (SP)]

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:
>* 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