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--- news:news [2021/04/25 21:58] – Wolfgang Viechtbauer
+++ news:news [2021/06/09 12:58] – Wolfgang Viechtbauer
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 ~~NOTOC~~
+==== June 9th, 2021: Version 3.0 Released on CRAN ====
+A new version of the metafor package (version 3.0) has been published on CRAN. This version includes a lot of updates that have accumulated in the development version of the package over the past 14-15 months. Some highlights:
+  * The documentation has been further improved. I now make use of the [[https://cran.r-project.org/package=mathjaxr|mathjaxr]] package to nicely render equations in the HTML help pages (and in order to do this, I had to create the mathjaxr package in the first place!).
+  * ''selmodel()'' was added for fitting a wide variety of selection models, including the beta selection model by Citkowicz and Vevea (2017), various models described by Preston et al. (2004), and step function models (with the three-parameter selection model (3PSM) as a special case).
+  * As another technique related to publication/small-sample bias, the ''tes()'' function was added to carry out the test of 'excess significance' (Ioannidis & Trikalinos, 2007; see also Francis, 2013).
+  * The ''regtest()'' function now shows the 'limit estimate' of the (average) true effect/outcome. This is in essence what the PET/PEESE methods do (when the standard errors / sampling variances are used as predictors in a meta-regression model).
+  * One can now also fit so-called 'location-scale models' via the ''rma()'' function (using the ''scale'' argument). With this, one can specify predictors for the amount of heterogeneity in the outcomes (to examine if the outcomes are more/less heterogeneous under certain circumstances).
+  * The ''regplot()'' function can be used to draw bubble plots based on meta-regression models. For models involving multiple predictors, the function draws the line for the 'marginal relationship' of a predictor. Confidence/prediction interval bands can also be shown.
+  * Two functions were added that are related to the meta-analysis of correlation matrices / regression coefficients: ''rcalc()'' for calculating the var-cov matrix of correlation coefficients and ''matreg()'' for fitting regression models based on correlation/covariance matrices.
+  * Sometimes, it might be necessary to aggregate a meta-analytic dataset with multiple outcomes from the same study to the study level. An ''aggregate()'' method for ''escalc'' objects was added that can do this, while (approximately) accounting for various types of dependencies.
+  * When using functions that allow for parallel processing, progress bars can now also be shown, thanks to the [[https://cran.r-project.org/package=pbapply|pbapply]] package. Gives you an idea whether to just grab a coffee or go out for lunch while your computer is chugging along.
+  * 24 new datasets were added (there are now over 60 datasets included in the package). These datasets also cover advanced methodology, such as multivariate/multilevel models, network meta-analysis, phylogenetic meta-analysis, and models with a spatial correlation structure.
+Lots of smaller tweaks/improvements were also made. I feel like so much has accumulated that this warranted a version jump to version 3.0.
 ==== April 21st, 2021: Better Degrees of Freedom Calculation ====