[R-meta] Question about function reporter()

Fri, Jun 16, 2023 1:44 AM

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 be
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 the
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

________________________________________
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> on behalf
of Viechtbauer, Wolfgang (NP) via R-sig-meta-analysis <r-sig-meta-analysis at r-
project.org>
Sent: Thursday, 15 June 2023 18:38
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-
project.org>
Cc: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl>;
Gabriel Cotlier <gabiklm01 at gmail.com>
Subject: Re: [R-meta] Question about function reporter()

Dear Gabriel,

You can't, since reporter() doesn't currently work for 'rma.mv' objects.

Models that can be fitted with rma() (same as rma.uni()) are relatively simple
and the number of possibilities that need to be covered for translating the
results from such a model into text are managable. Although even here, there are
currently restrictions. For example, reporter() currently only works for
'intercept-only models' (i.e., models without moderators), it doesn't work when
robust() was used on the model, and it doesn't work for location-scale models.
Allowing reporter() to work with meta-regression models is on my radar, but not
sure when I will get to this.

Models that can be fitted with rma.mv() are an entirely different beast. This
function allows users to fit multilevel models (with essentially no limits on the
number of levels), multivariate models (with multiple correlated random effects),
network meta-analyses, phylogenetic meta-analyses, spatio-temporal models, models
with random slopes, models with crossed random effects, and combinations thereof
(e.g., multivariate network meta-analysis). Such models will also typically
involve one or multiple moderators (e.g., to distinguish different outcomes,
treatments, time points, etc.). Depending on the type of model, different aspects
of the results are also more or less relevant (e.g., in a phylogenetic MA, there
would be a lot of focus on the random effects for species, while in a network MA,
focus would be more on contrasting the different treatments with each other).
There is essentially no way in hell that one could write reporter()-like
functionality for 'rma.mv' type models that covers all these
aspects/possibilities in a sensible way.

Of course, one could consider writing a version that only covers a few special
cases; for example, models of the form rma.mv(yi, V, random = ~ 1 |
level1/level2/level3/...) or rma.mv(yi, V, random = ~ var1 | var2) although the
latter type of model would often be used when var1 corresponds to different
outcomes in which case the model would probably involve moderators and be of the
form rma.mv(yi, V, mods = ~ outcome, random = ~ outcome | study), but in the end,
the reporter() function cannot read the users mind as to what the goal and focus
of their analysis was.

Alternatively, one could generate very generic text that does cover many
possibilities, but this would add essentially nothing to just reading the output
directly.

Maybe if we wait another 20-30 years, ChatGPT (or Skynet or whatever it will be
called then) will be able to do something like this automatically. However, we
might be too busy fighting off the Terminators at that point to worry about
rma.mv() models ...

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Gabriel Cotlier via R-sig-meta-analysis
Sent: Thursday, 15 June, 2023 6:37
To: R Special Interest Group for Meta-Analysis
Cc: Gabriel Cotlier
Subject: [R-meta] Question about function reporter()

Hello all,

I am using an object of class "rma.mv" "rma" as :

class(data)
[1] "rma.mv" "rma"

and would like to use the function reporter().
How could this possibly be done either directly in metafor in R or maybe in
JAMOVI or in other software where the metafor package is included?

Thanks a lot.
Kind regards,
Gabriel

[R-meta] Question about function reporter()

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