-----Original Message-----
From: Gabriel Cotlier [mailto:gabiklm01 at gmail.com]
Sent: Friday, 16 June, 2023 11:45
To: Viechtbauer, Wolfgang (NP)
Cc: R Special Interest Group for Meta-Analysis
Subject: Re: [R-meta] Question about function reporter()
Hello?Wolfgang,
As far as I understand from your explanation, by setting random variables to
observe the potential influence?of whether?the correlations ( yi ) are
positive?or negative would not be a random model, is this correct?
But, what if I keep moderator for?grouping?by Type (categorical:? corresponding
to the method employed by the studies either "CS", "R", "E")? and would include
in random another "Id" that represent whether the correlations come from either
the same or a different?study by means of the variable named "Article"
(numerical: with same value for same article ) as follows:
res3a <-?rma.mv(yi = yi,
? ? ? ? ? ? ? ?V = vi,
? ? ? ? ? ? ? ?mods = ~Type - 1,
? ? ? ? ? ? ? ?random = list(~1 | alloc, ~1 | Article),
? ? ? ? ? ? ? ?data = dat)
Could now be considered?in this case a random effect model?
Thanks a lot.
Kind regards,
Gabriel
On Fri, Jun 16, 2023 at 11:45?AM Viechtbauer, Wolfgang (NP)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
As for your actual question: That's a bit too broad. Essentially, you need to
familiarize yourself with what people typically report for standard RE models (as
reporter() does), then familiarize yourself with what people report meta-
regression models (since you have a meta-regression model), and then consider how
the random effects structure of your model differs from a standard RE model and
how this might affect what to report. I am not aware of any papers that will walk
you through all of that. People typically learn reporting practices from what
other people have done, so reading lots of existing meta-analyses will give you a
sense of how this is done.
This aside, I am not sure what you hope to accomplish by adding a random effect
for whether the outcome is positive or negative. Also, your model does not
capture any heterogeneity beyond this, so it isn't really a random-effects model
(or something akin to it).
Best,
Wolfgang
-----Original Message-----
From: Gabriel Cotlier [mailto:gabiklm01 at gmail.com]
Sent: Friday, 16 June, 2023 9:08
To: Yefeng Yang
Cc: R Special Interest Group for Meta-Analysis; Viechtbauer, Wolfgang (NP)
Subject: Re: [R-meta] Question about function reporter()
Hello,
Wolfgang : very helpful and nourishing knowledge and guidance about the
function?rma.mv() potential and complexity, thanks a lot for the explanation!
Yes indeed, maybe in the "longue dur?e"?--or not so much--?future time we will
more worried?about bigger threats AI technology?can pose to us ...
Anyway, It become an interesting?participative?discussion afterwards.
Maybe, I should apologize due to the lack of specificity or rugurosity in my
question, since I was only thinking?--but did not write it--in my particular
case, mainly of an rma.rm() function with the simplest the possible "random"
arguments rather than?the more the complex nested random?effect models, such as
for instance:
data_1 <-?rma.mv(yi = yi,
? ? ? ? ? ? ? ? ? ? ?V = vi,
? ? ? ? ? ? ? ? ? ? ?mods = ~Type - 1,
? ? ? ? ? ? ? ? ? ? ?random = ~1 | alloc,
? ? ? ? ? ? ? ? ? ? ?data = dat)
where the "alloc" variable refers just whether?the correlation ( yi ) has either
positive or negative sign (numerical variable? taking either -1 or 1) and "Type"
is a just categorical variable (of char class) composed of 3 clases Types namly
"R", "E", and "CS".
Maybe there is instead?of a reporter() function?output results some bibliography
that can lead me to a nice manner in which I can report the results of my simple
application of?rma.mv() function?output?as an example to support the bases?of
writing of my report.
Thanks a lot.
Kind regards,
Gabriel
On Thu, Jun 15, 2023 at 12:05?PM Yefeng Yang <yefeng.yang1 at unsw.edu.au> wrote:
Actually, I have a different opinion about?reporter() function. Just for an open
discussion and no offensive.?Instead of automatically generating an analysis
report based on the fitted model (via rma()), it is probably more useful to have
a helper function to automatically generate a "publication-ready" table that
shows the quantities recommended by various PRISMA-related reporting guidelines,
such as?the name of the moderator, tau, I2, point estimate, CIs, k, t, p, et al.
The analysis report is something that should be (and must be at some point) done
by the analysts themselves and they are responsible for the proper
interpretation.
Regards,
Yefeng