[R-meta] The phylogenetic signal of a single trait and its significance

Dear Wolfgang,


That's great! I think it makes sense as the phylogeny variance is eithor very low or zero as well when I replace the trait Y with other representations in the models. Thank you for helping me work things out!!




Cheers!
Pengzhen


---- Replied Message ----
| From | Viechtbauer, Wolfgang (NP)<wolfgang.viechtbauer at maastrichtuniversity.nl> |
| Date | 11/30/2023 08:40 |
| To | R Special Interest Group for Meta-Analysis<r-sig-meta-analysis at r-project.org> |
| Cc | Pengzhen Huang<maiqi1317 at 163.com> |
| Subject | RE: [R-meta] The phylogenetic signal of a single trait and its significance |
Dear Pengzhen,

Cerrtainly, variance components (including the one for phylogeny) can be essentially zero. That is what is happening here. So nothing unusual about that. Whether this makes sense in the present context I cannot judge.

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> On Behalf
Of Pengzhen Huang via R-sig-meta-analysis
Sent: Thursday, November 30, 2023 14:30
To: r-sig-meta-analysis at r-project.org
Cc: Pengzhen Huang <maiqi1317 at 163.com>
Subject: Re: [R-meta] The phylogenetic signal of a single trait and its
significance

Dear Wolfgang,

(Sorry that I'm not familiar with the operations!) Great thanks for the
reminder! I set wrong random factors before. Based on the R code provided in OSF
of your paper, I corrected my code and reran my models. Here are the codes from
building the tree to running the full models (with all moderators):

primatetree <- compute.brlen(primatetree1)
A <- vcv(primatetree, corr=TRUE)
dat$phylo <- dat$Species
nonphy<-
rma.mv(ES,variance,data=dat,mods=~Y+X1+X2+X3+X4,random=list(~1|Species/Group))

nonphy
Multivariate Meta-Analysis Model (k = 152; method: REML)

Variance Components:
estim    sqrt   nlvls fixed        factor
sigma^2.1  0.0484   0.2201   28    no         Species
sigma^2.2  0.0199   0.1412   63    no   Species/Group
........

phy<-
rma.mv(ES,variance,data=dat,mods=~Y+X1+X2+X3+X4,random=list(~1|Species/Group,~1|
phylo),R=list(phylo=A))
phy
Multivariate Meta-Analysis Model (k = 152; method: REML)
Variance Components:
estim    sqrt   nlvls fixed        factor     R
sigma^2.1  0.0484   0.2201   28    no         Species    no
sigma^2.2  0.0199   0.1412   63    no   Species/Group    no
sigma^2.3  0.0000   0.0000   28    no           phylo   yes
....

logLik(nonphy)-logLik(phy)
'log Lik.' 7.11124e-09 (df=16)
anova.rma(nonphy,phy)
df    AIC      BIC     AICc    logLik    LRT   pval     QE
Full    17 208.0528 257.8162 213.1528 -87.0264               217.0285
Reduced 16 206.0528 252.8889 210.5487 -87.0264 0.0000 1.0000 217.0285