[R-meta] Fwd: Overlapping CIs with significant difference among subgroups
Dear Dr. Wolfgang, I implemented your suggestions and obtained some different results. I found a difference in the variable field, for example, which represents whether the data was collected in a laboratory (no) or in the field (yes). Therefore, the source of the data may introduce a noise in the estimation of an average effect size. Since the moderator has only two levels, I cannot add it among random variables. Or is there a way of including field as a random variable (e.g. effectsizeID|field)? I can also add it as a fixed predictor. In this situation, how can I estimate the average effect size, because the intercept will represent one level of the moderator? I added the variable field to my dataset. Thank you in advance. Best wishes, Rafael. _______________________________________________________ *Prof. Dr. Rafael Rios Moura* *scientia amabilis * Coordenador de Pesquisa e do NEPEE/CNPq UEMG - Unidade Ituiutaba ORCID: http://orcid.org/0000-0002-7911-4734 Curr?culo Lattes: http://lattes.cnpq.br/4264357546465157 <http://orcid.org/0000-0002-7911-4734> <http://lattes.cnpq.br/4264357546465157> <http://lattes.cnpq.br/4264357546465157>Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2 <http://orcid.org/0000-0002-7911-4734> Rios de Ci?ncia: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg <http://orcid.org/0000-0002-7911-4734> Em ter., 6 de out. de 2020 ?s 16:17, Viechtbauer, Wolfgang (SP) < wolfgang.viechtbauer at maastrichtuniversity.nl> escreveu:
Dear Rafael,
The SEs of the predicted average outcomes for the various levels can be
quite different than the SEs of the difference between levels.
You can get the predicted average outcome for all four levels with:
pred.r = predict(res, transf=transf.ztor, digits=3, newmods =
rbind(c(0,0,0), c(1,0,0), c(0,1,0), c(1,1,1)))
pred.r
And then you can plot them with:
forest(pred.r$pred, ci.lb=pred.r$ci.lb, ci.ub=pred.r$ci.ub,
slab=c("Without grouping","Temporal grouping","Spatial grouping", "Both"))
Indeed, CIs are wide and overlap. But let's now compute the predicted
average difference between levels when compared against the "Without
grouping" level:
pred.r = predict(res, transf=transf.ztor, digits=3, newmods =
rbind(c(1,0,0) - c(0,0,0), c(0,1,0) - c(0,0,0), c(1,1,1) - c(0,0,0)),
intercept=FALSE)
pred.r
forest(pred.r$pred, ci.lb=pred.r$ci.lb, ci.ub=pred.r$ci.ub, slab=c("Diff
Temporal grouping","Diff Spatial grouping", "Diff Both"))
Now the CIs are quite narrow and exlude 0.
This aside, I would recommend that you include random effects for species
twice, once without and once with the phylogenetic correlation matrix:
h$speciesIDnon <- h$speciesID
res <- rma.mv(zf, vzf, mods=~sce_temporal*sce_spatial, random = list
(~1|effectsizeID, ~1|studyID, ~1|speciesIDnon, ~1|speciesID),
R=list(speciesID=corr), data=h)
This is model (15) from:
Nakagawa, S., & Santos, E. S. A. (2012). Methodological issues and
advances in biological meta-analysis. Evolutionary Ecology, 26(5),
1253-1274.
Conclusions do not change as far as I can tell, but I would still go with
that model. A LRT also shows that this model fits significantly better:
res0 <- rma.mv(zf, vzf, mods=~sce_temporal*sce_spatial, random = list
(~1|effectsizeID, ~1|studyID, ~1|speciesID), R=list(speciesID=corr), data=h)
anova(res, res0)
Best,
Wolfgang
-----Original Message----- From: Rafael Rios Moura [mailto:biorafaelrm at gmail.com] Sent: Tuesday, 06 October, 2020 20:25 To: r-sig-meta-analysis at r-project.org; Viechtbauer, Wolfgang (SP) Subject: Fwd: Overlapping CIs with significant difference among subgroups ATTACHMENT(S) REMOVED: dataset.csv | pruned_super-tree.tre | script.R Dear Wolfgang and All, Few months ago, I sent this email about a result obtained from a mixed effects MLMA, controlling for phylogenetic non-independence. I tested the difference between two levels of a moderator and obtained two close means (0.39 and 0.31) with highly overlapping CIs. However, the omnibus test detected a difference between estimates. Could it be a problem with my
code
or the test? Or am I not using the "predict" function correctly? My
dataset
and script are attached. I am grateful for contributions. Best wishes,
_______________________________________________________ Prof. Dr. Rafael Rios Moura scientia amabilis Coordenador de Pesquisa e do NEPEE/CNPq UEMG - Unidade Ituiutaba ORCID: http://orcid.org/0000-0002-7911-4734 Curr?culo Lattes: http://lattes.cnpq.br/4264357546465157 Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2 Rios de Ci?ncia: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg ---------- Forwarded message --------- De: Rafael Rios <biorafaelrm at gmail.com> Date: seg., 1 de jun. de 2020 ?s 16:53 Subject: Overlapping CIs with significant difference among subgroups To: <r-sig-meta-analysis at r-project.org>, Viechtbauer Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl> Dear Wolfgang and All, I conducted a multilevel mixed-effects meta-analysis and found differences between levels of two moderators. I was expecting to find non-overlapped confidence intervals. However, I obtained overlapped confidence intervals for all subgroups. How can I interpret these results? In such situation, should I trust in the Q-test or in the CIs? I controlled for phylogenetic non-independence. Is there a chance of this approach affect the estimation of CIs using predict function? My dataset and script are attached. Best wishes, _______________________________________________________ Prof. Dr. Rafael Rios Moura Coordenador de Pesquisa e do NEPEE/CNPq Laborat?rio de Ecologia e Zoologia (LEZ) UEMG - Unidade Ituiutaba ORCID: http://orcid.org/0000-0002-7911-4734 Curr?culo Lattes: http://lattes.cnpq.br/4264357546465157 Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2 Rios de Ci?ncia: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg
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