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news:news2020 [2021/04/25 10:54]
Wolfgang Viechtbauer created
news:news2020 [2021/06/09 12:56]
Wolfgang Viechtbauer [March 19th, 2020: News Version (2.4-0) on Its Way to CRAN]
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 As a follow-up to yesterday's note, it is maybe worth mentioning that I also added two functions that are especially useful for those conducting network meta-analyses with the metafor package. With the ''to.wide()'' function, one can rearrange a dataset that is in an arm-based 'long' format to a contrast-based 'wide' format. Two examples illustrating the use of this function can be found under [[https://wviechtb.github.io/metafor/reference/to.wide.html|help(to.wide)]] (the link takes you to the corresponding help file, which is nicely formatted and shows the output of the examples). Once the dataset is in such a wide format, an important next step is the construction of variables that reflect which two groups are being compared with each other in each row (through +1, 0, -1 coding). Such a contrast matrix can be easily created with the ''contrmat()'' function. See [[https://wviechtb.github.io/metafor/reference/contrmat.html|help(contrmat)]] for the help file and two examples illustrating its use. The analysis of these two datasets (using arm- and contrast-based models) are illustrated under [[https://wviechtb.github.io/metafor/reference/dat.hasselblad1998.html|help(dat.hasselblad1998)]] and [[https://wviechtb.github.io/metafor/reference/dat.hasselblad1998.html|help(dat.hasselblad1998)]]. As a follow-up to yesterday's note, it is maybe worth mentioning that I also added two functions that are especially useful for those conducting network meta-analyses with the metafor package. With the ''to.wide()'' function, one can rearrange a dataset that is in an arm-based 'long' format to a contrast-based 'wide' format. Two examples illustrating the use of this function can be found under [[https://wviechtb.github.io/metafor/reference/to.wide.html|help(to.wide)]] (the link takes you to the corresponding help file, which is nicely formatted and shows the output of the examples). Once the dataset is in such a wide format, an important next step is the construction of variables that reflect which two groups are being compared with each other in each row (through +1, 0, -1 coding). Such a contrast matrix can be easily created with the ''contrmat()'' function. See [[https://wviechtb.github.io/metafor/reference/contrmat.html|help(contrmat)]] for the help file and two examples illustrating its use. The analysis of these two datasets (using arm- and contrast-based models) are illustrated under [[https://wviechtb.github.io/metafor/reference/dat.hasselblad1998.html|help(dat.hasselblad1998)]] and [[https://wviechtb.github.io/metafor/reference/dat.hasselblad1998.html|help(dat.hasselblad1998)]].
  
-==== March 19th, 2020: News Version (2.4-0) on Its Way to CRAN ====+==== March 19th, 2020: New Version (2.4-0) on Its Way to CRAN ====
  
 Just submitted a new version (2.4-0) to CRAN. This update was prompted by the upcoming change in R where the new  default will be ''stringsAsFactors=FALSE'' (at long last!). As a result, some tests were failing on R-devel, so these needed fixing. Along the way, I made various minor internal updates and added some convenience functionality to several functions. The full changelog can be found [[:updates#changes_in_version_24-0_2020-03-19|here]]. Just submitted a new version (2.4-0) to CRAN. This update was prompted by the upcoming change in R where the new  default will be ''stringsAsFactors=FALSE'' (at long last!). As a result, some tests were failing on R-devel, so these needed fixing. Along the way, I made various minor internal updates and added some convenience functionality to several functions. The full changelog can be found [[:updates#changes_in_version_24-0_2020-03-19|here]].
  
news/news2020.txt ยท Last modified: 2021/08/22 21:20 by Wolfgang Viechtbauer