[R-meta] Question about function reporter()

[Gabriel Cotlier]

Hello Wolfgang,

Thank you very much for the explanation  and the link. I will go through it
carefully.

Briefly, I was trying to use '~ 1 | alloc'  (with alloc being a column in
the table class numerical taking the sing of the correlation either -1 or
1)  to model whether the influence of the correlations' sing  hold for the
alternative hypothesis that when positive the correlations --which are
coming from different studies (or experiments in the studies)-- are the
result of correlating a magnitud A with B; whereas when negative the
correlations comes from correlating the same source A source with C.
Thanks a lot again.
Kind regards,
Gabriel



On Fri, Jun 16, 2023 at 2:34 PM Viechtbauer, Wolfgang (NP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> There is no universal definition of what a random-effects model is, but
> take a look at:
>
> https://www.metafor-project.org/doku.php/analyses:crede2010
>
> and especially the section "A Common Mistake when Fitting the Multilevel
> Model". So, if your data have such a multilevel structure, then typically
> we would add a random effect for articles and a random effect for the
> observations within articles. Beyond this, you could do '~ 1 | alloc'
> although it is still not clear to me what you think this is modelling.
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: Gabriel Cotlier [mailto:gabiklm01 using 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 using 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 using 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 durée" --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 using 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 using r-project.org>
> on behalf
> >>of Viechtbauer, Wolfgang (NP) via R-sig-meta-analysis
> <r-sig-meta-analysis using r-
> >>project.org>
> >>Sent: Thursday, 15 June 2023 18:38
> >>To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis using r-
> >>project.org>
> >>Cc: Viechtbauer, Wolfgang (NP) <
> wolfgang.viechtbauer using maastrichtuniversity.nl>;
> >>Gabriel Cotlier <gabiklm01 using 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 using 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
>

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