[R-meta] metafor::matreg() and its workflow

[Viechtbauer, Wolfgang (SP)]

Hi Stefanou,

They address very different questions, so I would say neither is more useful than the other.

Best,
Wolfgang

>-----Original Message-----
>From: Stefanou Revesz [mailto:stefanourevesz using gmail.com]
>Sent: Monday, 13 December, 2021 22:15
>To: Viechtbauer, Wolfgang (SP)
>Cc: R meta
>Subject: Re: metafor::matreg() and its workflow
>
>Super helpful! For some reason, the devel version doesn't get
>installed on my machine (must be an R issue; mine's a version 4.0).
>
>At some point, one might say which regression is more useful, the one
>on the means from the fixed effects or the one on the true effects
>from the random effects!
>
>rma.mv(yi ~ 0 + outcome*group, V, random = ~ 0 + outcome*group |
>study, struct = "GEN")
>
>Thank you so very much!
>Stefanou
>
>On Mon, Dec 13, 2021 at 2:59 PM Viechtbauer, Wolfgang (SP)
><wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
>>
>> Here is an example using G as input to matreg():
>>
>> https://www.metafor-
>project.org/doku.php/analyses:vanhouwelingen2002#regression_of_true_log_odds
>>
>> (you will need the devel version of metafor for the cvvc="varcov" part).
>>
>> Best,
>> Wolfgang
>>
>> >-----Original Message-----
>> >From: Stefanou Revesz [mailto:stefanourevesz using gmail.com]
>> >Sent: Monday, 13 December, 2021 21:20
>> >To: Viechtbauer, Wolfgang (SP)
>> >Cc: R meta
>> >Subject: Re: metafor::matreg() and its workflow
>> >
>> >Thank you so much! One clarification question. matreg() is not
>> >effect-size specific, correct? I mean you may have meta-analyzed any
>> >type effect size (SMD, ROM, OR, ...) and then subject the vcov() or G
>> >or H matrices of those meta-analyses to matreg(), correct?
>> >
>> >Thanks again,
>> >Stefanou
>> >
>> >On Mon, Dec 13, 2021 at 12:53 PM Viechtbauer, Wolfgang (SP)
>> ><wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
>> >>
>> >> There is an upcoming talk by Suzanne Jak on MASEM at this seminar series:
>> >>
>> >> https://www.srmasig.org/seminar/
>> >>
>> >> Might be of interest.
>> >>
>> >> Best,
>> >> Wolfgang
>> >>
>> >> >-----Original Message-----
>> >> >From: Stefanou Revesz [mailto:stefanourevesz using gmail.com]
>> >> >Sent: Thursday, 09 December, 2021 23:23
>> >> >To: Viechtbauer, Wolfgang (SP)
>> >> >Cc: R meta
>> >> >Subject: Re: metafor::matreg() and its workflow
>> >> >
>> >> >Dear Wolfgang,
>> >> >
>> >> >I see, so conditioning (using predict() ) is the way to go even if
>> >> >there is a large set of conditions.
>> >> >
>> >> >Related to the above, if instead of vcov(), one intends to use G and H
>> >> >matrices (latent regression), would that also require conditioning on
>> >> >the levels of fixed effects?
>> >> >
>> >> >The other challenge that I expect to encounter (I'm preparing to do a
>> >> >meta-analysis exploring anxiety and achievement) is that correlations
>> >> >reported in each study may not reflect the same pair of variables
>> >> >across the studies. Thus, this prevents me from having a "var1.var2"
>> >> >like variable in my model which also means I can't proceed to mateg().
>> >> >I believe, in that case, I can do only an exploratory study of
>> >> >correlations (with rma.mv() ) rather than a model based one (with
>> >> >matreg() ).
>> >> >
>> >> >Thank you,
>> >> >Stefanou