-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Viechtbauer, Wolfgang (NP) via R-sig-meta-analysis
Sent: Thursday, 28 September, 2023 10:36
To: r-sig-meta-analysis at r-project.org
Cc: Viechtbauer, Wolfgang (NP)
Subject: [R-meta] New version of the metafor package (4.4-0) released on CRAN
Hi all,
It might be of intererest to some of you that a new version of the metafor
package has been released on CRAN. Some of the more important/interesting updates
to the package include:
* The older (convoluted) way of setting some package options has been replaced
by two functions, getmfopt() and setmfopt(), for getting and setting package
options. This new approach makes use of the standard way of setting options in R
(see help(options)). Also, some of the options that can be set in this way are
now more flexible.
* The fsn() function can now carry out a fail-safe N calculation based on a
random-effects model (when using 'type="General"'). This is a generalization of
the Orwin and Rosenberg methods, which is an interesting methodological
development in itself.
* The theming of all plots (based on the foreground and background colors of
the plotting device) has been further improved. Within RStudio, plot colors can
now also be automatically set based on the theme (with setmfopt(theme="auto")).
* The various forest() functions now have an additional argument called
'tabfig', which makes it easier to exactly align the numbers in the annotations
on the right-hand side.
* The addpoly.default() and addpoly.rma.predict() functions gain a 'constarea'
argument, for the option to draw the polygons with a constant area. This idea
arose from a discussion on Mastodon -
https://scholar.social/@wviechtb/111131706271083360 - about drawing so-called
'diamond plots' (see https://psyarxiv.com/fzh6c for more details about such
plots). The idea is that, by default, the eyes of the person looking at a plot
are automatically drawn to the polygons that have a wider confidence interval
(which occupy a larger area on the plot), which is actually the opposite of what
you want to happen (since estimates with wider confidence intervals are less
precise). By making the area of the polygons constant (which requires reducing
their height according to the interval widths), this undesired effect can be
compensated to some extent.
* Two new measures have been added to escalc(), namely "R2" and "ZR2", for
meta-analyzing coefficients of determination (but read the caveats mentioned
under help(escalc) with respect to these measures).
* For measures "PCOR", "ZPCOR", "SPCOR", and "ZSPCOR", argument 'mi' in
escalc() now refers to the total number of predictors in the regression models
(i.e., also counting the focal predictor of interest). This is a non-backwards
compatible change (which I really try to avoid), but in this case this was
important for consistency with other measures/equations. The change is also very
minor, since 'mi' always appears in equations as a value that is subtracted from
'ni' (the sample size) and since the latter is (hopefully) large relative to
'mi', the impact of this change should be very minor.
* The suite of automated package tests now also includes automated visual
comparison tests of plots. Therefore, any changes I make to the package that
unintentionally break a particular plotting function are now automatically
detected.
The full changelog of this (and all prior versions) can be found here:
https://wviechtb.github.io/metafor/news/index.html
Best,
Wolfgang
--
Wolfgang Viechtbauer, PhD, Statistician | Department of Psychiatry and
Neuropsychology | Maastricht University | PO Box 616 (VIJV1) | 6200 MD
Maastricht, The Netherlands | +31(43)3884170 | https://www.wvbauer.com