[R-meta] min sample size for three random variables in meta-analysis

[Jose Valdebenito]

Dear Michael,
Thanks for your reply. By sample size I mean small number of primary
studies. k means number of effect sizes.
In the example below there were 10 effect sizes, 7 studies, 9 species
ID, and 9 species associated with a vcv value.

> head(df, 10)
species_2 | spp | study.ID | L_d | L_v
Grus_americana | Grus_americana | p.b.4 | 0.000 | 0.135
Loxia_leucoptera | Loxia_leucoptera | p.b.15 | 1.057 | 0.068
Centrocercus_urophasianus | Centrocercus_urophasianus | p.b.60 | 0.384 | 0.021
Pica_nuttalli | Pica_nuttalli | p.b.8 | -2.042 | 0.037
Acrocephalus_paludicola | Acrocephalus_paludicola | 17 | 0.000 | 0.068
Acrocephalus_paludicola | Acrocephalus_paludicola | 17 | -4.978 | 0.334
Lepidothrix_coronata | Lepidothrix_coronata | 20 | -2.043 | 0.088
Erithacus_rubecula | Erithacus_rubecula | 35 | -1.723 | 0.401
Fringilla_coelebs | Fringilla_coelebs | 35 | -2.697 | 0.111
Parus_caeruleus | Parus_caeruleus | 35 | 4.862 | 0.559

Thanks,
Jose
On Fri, 22 Jul 2022 at 08:19, Michael Dewey <lists using dewey.myzen.co.uk> wrote:
>
> Dear Jose
>
> Unfortunately this is a plain text list and your post in HTML has got
> scrambled so as to be almost unreadable.
>
> Just to clarify, when you say small sample size do you mean a small
> number of primary studies or that individual studies were based on small
> numbers? Is k the number of primary studies?
>
> Michael
>
> On 21/07/2022 15:42, Jose Valdebenito wrote:
> > Hi,
> >
> > I am conducting a (multi-level) meta-analysis with some sample sizes that
> > are a bit small.
> >
> > I was wondering if there is a kind of rule of thumb regarding minimum
> > sample size number, and the maximum number of random variables I can add to
> > the models.
> >
> > I would like to add 3 (as suggested in Cinar et al. Methods Ecol Evol.
> > 2022;13:383–95), but I am afraid that might incur in overparameterization
> > if I have, say k=10?
> >
> > These are the random variables:
> > -Phylogenetic relatedness
> > -Study ID
> > -Species ID
> >
> > Also, would it be any different in a meta-regression?
> >
> > Here I paste the model and dataset so you can see:
> >
> > m2 <- rma.mv(L_d, L_v,
> >                          data = df,
> >                           random = list(~1|species_2,
> >                                                 ~1|study.ID,
> >                                                 ~1|spp),
> >                            R = list(species_2 = vcv), digits = 3)
> >
> >
> >> head(df, 10)
> > species_2                                 spp
> >             study.ID         L_d         L_v
> > Grus_americana                       Grus_americana
> > p.b.4             0.000       0.135
> > Loxia_leucoptera                      Loxia_leucoptera
> > p.b.15          1.057        0.068
> > Centrocercus_urophasianus    Centrocercus_urophasianus   p.b.60
> > 0.384        0.021
> > Pica_nuttalli                              Pica_nuttalli
> >          p.b.8            -2.042      0.037
> > Acrocephalus_paludicola          Acrocephalus_paludicola       17
> >      0.000      0.068
> > Acrocephalus_paludicola          Acrocephalus_paludicola       17
> >        -4.978      0.334
> > Lepidothrix_coronata                Lepidothrix_coronata              20
> >               -2.043     0.088
> > Erithacus_rubecula                   Erithacus_rubecula                35
> >                -1.723      0.401
> > Fringilla_coelebs                       Fringilla_coelebs
> >   35                 -2.697      0.111
> > Parus_caeruleus                       Parus_caeruleus                    35
> >                 4.862      0.559
> >
> >
> > Thanks in advance,
> > Joe
> >
> >       [[alternative HTML version deleted]]
> >
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>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html