[R-meta] phylogenetic information in both moderator and random part of rma.mv?
Viechtbauer, Wolfgang (NP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Fri Sep 30 11:44:40 CEST 2022
Sounds reasonable.
One additional thing: I don't know what your data structure actually looks like. Is each row a different study? Or is each row a different species? If not, then I would strongly suggest to include '~ 1 | id' where
Final.data$id <- 1:nrow(Final.data)
as a random effect (in both mod1 and mod2). Otherwise you would be assuming homogeneity of true outcomes within studies/species, which is a strong assumption.
Best,
Wolfgang
>-----Original Message-----
>From: Sigurd Einum [mailto:sigurd.einum using ntnu.no]
>Sent: Friday, 30 September, 2022 10:26
>To: Viechtbauer, Wolfgang (NP); r-sig-meta-analysis using r-project.org
>Subject: RE: phylogenetic information in both moderator and random part of
>rma.mv?
>
>Dear Wolfgang, thank you for these insights! This clarified for me the way
>effects of class and phylogeny (within class) is partitioned in the model!
>When I fit the two models you suggested (see below), AICc is lower for mod2 (with
>delta AICc > 2). My interpretation of your reply, i.e. that the effect of
>phylogeny is an empirical question, is that since there is little evidence for a
>phylogenetic signal within classes for this data set, mod2 (i.e. treating the
>species as independent observations as long as I account for the random species
>effect (1|species)) is appropriate when estimating the class effect.
>
>mod1 <- rma.mv(lambda, sampvar,mods = ~ Class, random = list(~ 1 | study, ~ 1 |
>species, ~ 1 | phylo),
> R = list(phylo = A), data = Final.data, sparse = TRUE, method =
>"REML")
>
>mod2 <- rma.mv(lambda, sampvar,mods = ~ Class, random = list(~ 1 | study, ~ 1 |
>species),
> data = Final.data, sparse = TRUE, method =
>"REML")
>
>Best wishes,
>Sigurd
>
>>-----Original Message-----
>>From: Viechtbauer, Wolfgang (NP)
>><wolfgang.viechtbauer using maastrichtuniversity.nl>
>>Sent: Thursday, September 29, 2022 4:59 PM
>>To: r-sig-meta-analysis using r-project.org
>>Cc: Sigurd Einum <sigurd.einum using ntnu.no>
>>Subject: RE: phylogenetic information in both moderator and random part of
>>rma.mv?
>>
>>Dear Sigurd,
>>
>>I do not know enough about the specifics of the application to say whether
>>comparing the model with versus without phylogeny is sufficient to conclude
>>something about evolutionary divergence.
>>
>>However, let me make a few comments (I am also basing some comments here
>>on what you wrote to me initially in an email before redirecting you to this
>>mailing list for further discussions):
>>
>>So you fitted a mixed-effects model with lme() of the form:
>>
>>lme(Y ~ Class, random = ~ 1 | species, data=Final.data, method="ML")
>>
>>(or maybe including weights = varFixed(~ sampvar)) and found 'Class' to be
>>relevant (regardless of whether this means: large coefficient, statistically
>>significant, sufficiently larger value of the information criterion compared to
>a
>>null model). Then you fitted the model below (where you are accounting for
>>phylogeny) and now the support for the relevance of 'Class' disappears or is
>>considerably weaker. I hope this summarizes the issue.
>>
>>First, I would ask: Have you compared the lme() model with this?
>>
>>rma.mv(Y, sampvar, mods = ~ Class, random = ~ 1 | species, data = Final.data,
>>sparse = TRUE, method = "ML")
>>
>>Note that this is not exactly the same model as what lme() fits as explained
>here:
>>
>>https://www.metafor-project.org/doku.php/tips:rma_vs_lm_lme_lmer
>>
>>This aside, it is quite possible that the relevance / effect / significance of
>'Class'
>>changes when accounting for the phylogeny, because this accounts for the
>>potential dependence of the outcome due to similarities between species in a
>>different way than just including species itself as a random effect.
>>
>>Now does it make sense to include Class as a moderator while also including
>>random effects for species? I would say yes. Class is a broader category, so the
>>species random effect accounts for heterogeneity within classes (and the fixed
>>effect for class allows the average of all species belonging to the same class
>to
>>differ from that of other classes). And whether the values of this random effect
>>are correlated or not (as predicted by the phylogeny) is an empirical question.
>So
>>if the model with phylogeny fits better, then I would go with that.
>>
>>Best,
>>Wolfgang
>>
>>>-----Original Message-----
>>>From: R-sig-meta-analysis
>>>[mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Sigurd
>>>Einum
>>>Sent: Wednesday, 28 September, 2022 21:04
>>>To: r-sig-meta-analysis using r-project.org
>>>Subject: [R-meta] phylogenetic information in both moderator and random
>>>part of rma.mv?
>>>
>>>Dear list,
>>>
>>>I want to test for evolutionary divergence (among ectothermic animals)
>>>in a single trait Y. My first approach to this was to test for
>>>divergence among taxonomic classes (specifically amphibians, reptiles,
>>>insects, fish, and crustaceans). I compiled data on several species per
>>>class, and multiple estimates of Y per species (from different
>>>experiments), and analysed the data using a traditional mixed effects
>>>model (lme), with species as a random effect and taxonomic class as fixed
>>effect.
>>>
>>>However, one reviewer suggested I should control for phylogeny (without
>>>being more specific). So I built a tree for these species (using
>>>package rotl), made it ultrametric (using compute.brlen in package
>>>ape), and computed the variance- covariance matrix A from this (using
>>>vcv from package ape). I then created a variable phylo to distinguish
>>>the phylogenetic component from the non- phlylogenetic species random
>>effect, and used metafor to fit the model:
>>>
>>>rma.mv(Y, sampvar,mods = ~ Class, random = list(~ 1 | species, ~ 1 | phylo),
>>> R = list(phylo = A), data = Final.data, sparse = TRUE,
>>>method =
>>>"ML")
>>>
>>>(sampvar is the sampling variance associated with each estimate of Y)
>>>
>>>However, now I have started doubting whether this model makes sense,
>>>i.e. to estimate an effect of taxonomic class (which in essence is a
>>>phylogenetic effect) while simultaneously modelling a random effect of
>>>phylogeny. Would an appropriate alternative be to not have class as a
>>>moderator, but rather compare fits of models with and without the
>>>phylogenetic variance-covariance matrix. If the model including
>>>phylogeny is better than one without it, can I conclude that there is
>evolutionary
>>divergence in this trait?
>>>
>>>Any advice anyone might have on this would be much appreciated!
>>>
>>>Best wishes
>>>Sigurd Einum
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