[R-meta] New Version of metafor (2.0-0)

Viechtbauer Wolfgang (SP) wolfgang.viechtbauer at maastrichtuniversity.nl
Thu Jun 22 22:12:00 CEST 2017

This might be of interest to this list.

A new version of the metafor package is out (2.0-0). These are the changes:

Changes in Version 2.0-0 (2017-06-22)

   o added simulate() method for 'rma' objects; added MASS to 'Suggests'
     (since simulating for 'rma.mv' objects requires mvrnorm() from MASS)

   o cooks.distance.rma.mv() now works properly even when there are missing
     values in the data

   o residuals() gains 'type' argument and can compute Pearson residuals

   o the 'newmods' argument in predict() can now be a named vector or a
     matrix/data frame with column names that get properly matched up with
     the variables in the model

   o added ranef.rma.mv() for extracting the BLUPs of the random effects for
     'rma.mv' models

   o all functions that repeatedly refit models now have the option to show
     a progress bar

   o added ranktest.default(), so user can now pass the outcomes and
     corresponding sampling variances directly to the function

   o added regtest.default(), so user can now pass the outcomes and
     corresponding sampling variances directly to the function

   o funnel.default() gains 'subset' argument

   o funnel.default() and funnel.rma() gain 'col' and 'bg' arguments

   o plot.profile.rma() gains 'ylab' argument

   o more consistent handling of 'robust.rma' objects

   o added location-scale model

   o added a print method for 'rma.gosh' objects

   o the (log) relative risk is now called the (log) risk ratio in all help
     files, plots, code, and comments

   o escalc() can now compute outcome measures based on paired binary data
     ("MPRR", "MPOR", "MPRD", "MPORC", and "MPPETO")

   o escalc() can now compute (semi-)partial correlation coefficients
     ("PCOR", "ZPCOR", "SPCOR")

   o escalc() can now compute measures of variability for single groups
     ("CVLN", "SDLN") and for the difference in variability between two
     groups ("CVR", "VR"); also the log transformed mean ("MNLN") has been
     added for consistency

   o escalc() can now compute the sampling variance for measure="PHI" for
     studies using stratified sampling (vtpye="ST")

   o the `[` method for 'escalc' objects now properly handles the 'ni' and
     'slab' attributes and does a better job of cleaning out superfluous
     variable name information

   o added rbind() method for 'escalc' objects

   o added as.data.frame() method for 'list.rma' objects

   o added a new dataset (dat.pagliaro1992) for another illustration of a
     network meta-analysis

   o added a new dataset (dat.laopaiboon2015) on the effectiveness of
     azithromycin for treating lower respiratory tract infections

   o rma.uni() and rma.mv() now check if the ratio of the largest to
     smallest sampling variance is extreme large; results may not be stable
     then (and very large ratios typically indicate wrongly coded data)

   o model fitting functions now check if extra/superfluous arguments are
     specified via ... and issues are warning if so

   o instead of defining own generic ranef(), import ranef() from 'nlme'

   o improved output formatting

   o added more tests (but disabled a few tests on CRAN to avoid some issues
     when R is compiled with --disable-long-double)

   o some general code cleanup

   o renamed diagram_metafor.pdf vignette to just diagram.pdf

   o minor updates in the documentation


Wolfgang Viechtbauer, Ph.D., Statistician | Department of Psychiatry and    
Neuropsychology | Maastricht University | P.O. Box 616 (VIJV1) | 6200 MD    
Maastricht, The Netherlands | +31 (43) 388-4170 | http://www.wvbauer.com    

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