[R-meta] Issues when using rma.mv

[Michael Dewey]

Dear Diego

If you have all the raw data why do you not just analyse this as a 
multi-level mode (or mixed effects model)? Perhaps I have misunderstood 
here.

Incidentally your mailer is set to send HTML so your post is mangled 
since this is a plain text list.

Michael

On 19/05/2023 17:03, Diego Gallego García via R-sig-meta-analysis wrote:
> Good morning,
> 
> First post here, so I apologize if I do not explain my issue in the
> best way.
> 
> I am currently conducting a review on the length of the dependence period
> (time that the nestling spends with parents) in birds. I want to test which
> ecological factors affect this variable.
> 
> My raw dataset has one row per species and per study (i.e., there are some
> studies which account for more than one species, so I separate each species
> studied in each research), with its corresponding variables of the
> dependence period (PD: days), SD, N (number of individuals studied), etc...
> My raw dataset should look like this (dummy data):
> 
> Study_ID       Species      Latitude     Body weight      Status
>            DP        N        SD
> 1                    A                       50                3.4
>        Resident              45          3        1.81
> 2                    A                       38                3.4
>        Migrant                32          1         N/A
> 2                    B                        43               2.1
>        Migrant                33         11       3.45
> 3                    B                        38               2.1
>        Resident               38          6        2.45
> 3                    C                        12               3.6
>       Resident               159        2         0
> 
> Now, as you may see, there are some studies with an n=1 (only one
> individual was examined), so there is no valid SD for the study (i.e.,
> N/A). Thus, for the escalc() formula, I should delete them. But what about
> the last example? There were two individuals studied in that paper, and
> both yielded the same result, so the SD is roughly 0.
> 
> Afterwards, when using rma.mv for a mixed-effects model, those studies with
> SD=0 (then vi=0) are giving me problems. Specifically, there are some
> warnings in my models:
> 
> Warning messages:
> 1: There are outcomes with non-positive sampling variances.
> 2: 'V' appears to be not positive definite.
> 
> The model is the following:
> p1 <- rma.mv(data$yi, data$vi, mods= ~Latitude*Status,
>                 random=~1|Species, data=data)
> 
> Should I be worried about these warnings? Any way to fix them?
> 
> I appreciate any help.
> Best,
> *MSc Diego Gallego García*
> 
> Proyecto Águila del Chaco - Chaco Eagle Project
> Center for the Study and Conservation of Raptors in Argentina *(CECARA)*
> Institute of Earth and Environmental Sciences of La Pampa *(INCITAP)*
> National Scientific and Technical Research Council *(CONICET)*
> 
> <https://www.instagram.com/proyectoaguilachaco/>
> 
> diegothen using gmail.com
> https://www.researchgate.net/profile/Diego_Gallego_Garcia
> 
> 	[[alternative HTML version deleted]]
> 
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html