[R-meta] Why does rma.mv does not show the same results as robumeta?

[Cátia Ferreira De Oliveira]

Hello,

I have conducted a meta-analysis that I am currently analysing looking at
the relationship between memory and language/literacy and multiple studies
contributed more than one effect size. I have preregistered doing the
analyses in robumeta. But I am interested in checking how the results
converge across packages as I am tempted to use metafor for my next
meta-analysis given how easy it is to plot, check for publication bias, etc
with this package. When running both models, they produced
different results and I am a bit unsure as to why they are different. I
know if I look at the estimates it is not that different, but what
surprises me is the fact that DD has a higher estimate in one model but in
the other it is the DLD group. Maybe I have done something wrong. Does
anyone have any thoughts?






*# multilevel model looking at the relationship between memory and
language/literacy;# multiple studies have contributed multiple effect
sizeshead(Data)*[image: image.png]




*rma.model <- rma.mv <http://rma.mv>(yi, vi,  mods =  ~ factor(Group)-1,
 random= ~ 1 | Study/effectsizeID, data=Data)res*Multivariate Meta-Analysis
Model (k = 414; method: REML)

  logLik  Deviance       AIC       BIC      AICc
-13.0662   26.1323   36.1323   56.2253   36.2805

Variance Components:

            estim    sqrt  nlvls  fixed              factor
sigma^2.1  0.0109  0.1044     37     no               Study
sigma^2.2  0.0082  0.0903    414     no  Study/effectsizeID

Test for Residual Heterogeneity:
QE(df = 411) = 588.9613, p-val < .0001

Test of Moderators (coefficients 1:3):
QM(df = 3) = 11.1370, p-val = 0.0110

Model Results:

[image: Screenshot 2021-05-23 024135.png]

*robu.model <- robu(formula = yi ~ factor(Group)-1, data = Data,*
*                       studynum = Study, var.eff.size = vi,*
*                       rho = .8, small = TRUE)*
*print(robu.model)*

RVE: Correlated Effects Model with Small-Sample Corrections

Model: yi ~ factor(Group) - 1

Number of studies = 37
Number of outcomes = 414 (min = 1 , mean = 11.2 , median = 6 , max = 52 )
Rho = 0.8
I.sq = 52.35398
Tau.sq = 0.02918897

[image: image.png]

Thank you!

Best wishes,

Catia

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