[R-meta] PET-PEESE Question

[Viechtbauer, Wolfgang (NP)]

There is another issue:

Relationship$SE_Mod <- Relationship$vi^2

but the dataset is called "Relationship_TE_Occurrence".

Best,
Wolfgang

> -----Original Message-----
> From: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org> On Behalf
> Of Lukasz Stasielowicz via R-sig-meta-analysis
> Sent: Wednesday, December 6, 2023 08:53
> To: r-sig-meta-analysis using r-project.org
> Cc: Lukasz Stasielowicz <lukasz.stasielowicz using uni-osnabrueck.de>
> Subject: Re: [R-meta] PET-PEESE Question
>
> Dear Tori,
>
> vi refers to sampling variance in your code, right?
>
> In that case, slight code adjustments seem necessary:
> PET: mods = ~sqrt(vi) #standard error as a moderator
> PEESE: PET: mods = ~vi #variance as a moderator
>
>
> Further reading:
> https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/pub-bias.html#pet-
> peese
>
>
> Best,
> Lukasz
> --
> Lukasz Stasielowicz
> Osnabrück University
> Institute for Psychology
> Research methods, psychological assessment, and evaluation
> Lise-Meitner-Straße 3
> 49076 Osnabrück (Germany)
> Twitter: https://twitter.com/l_stasielowicz
> Tel.: +49 541 969-7735
>
> > Hello,
> >
> > Thank you again for all your guidance.
> >
> > I have been trying to conduct PET-PEESE analyses on several rma.mv objects
> > by adding variance as a moderator.  The following code works well:
> >
> > #pet-peese test
> > m_1_pet <- rma.mv(yi = yi,
> >                       V = vi,
> >                       mods = ~ vi,
> >                       slab = STUDY.ID,
> >                       data = Relationship_TE_Occurrence,
> >                       random = ~ 1 | STUDY.ID/EFFECT_SIZE_ID,
> >                       test = "t",
> >                       method = "REML")
> >
> > summary(m_1_pet, digits=3)
> >
> > However, when I try to conduct the PEESE part I receive this error message:
> > "Model matrix not of full rank. Cannot fit model" for the following code:
> >
> > Relationship$SE_Mod <- Relationship$vi^2
> >
> > m_1_peese <- rma.mv(yi = yi,
> >                       V = vi,
> >                       mods = ~ SE_Mod,
> >                       slab = STUDY.ID,
> >                       data = Relationship_TE_Occurrence,
> >                       random = ~ 1 | STUDY.ID/EFFECT_SIZE_ID,
> >                       test = "t",
> >                       method = "REML")
> >
> > summary(m_1_peese, digits=3)
> >
> > Does anyone have any insight into why the model would fit for the PET part
> > but not the PEESE? I'm not sure how to fix this issue.
> >
> > Thanks,
> > Tori