The metafor Package

A Meta-Analysis Package for R

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updates_old [2023/03/20 08:28] Wolfgang Viechtbauerupdates_old [2023/05/09 06:26] Wolfgang Viechtbauer
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 Older updates of the metafor package are archived on this page. More recent updates can be found [[updates|here]]. Older updates of the metafor package are archived on this page. More recent updates can be found [[updates|here]].
 +
 +==== Version 2.0-0 (2017-06-22) ====
 +
 +  * added ''simulate()'' method for ''rma'' objects; added ''MASS'' to ''Suggests'' (since simulating for ''rma.mv'' objects requires ''mvrnorm()'' from ''MASS'')
 +  * ''cooks.distance.rma.mv()'' now works properly even when there are missing values in the data
 +  * ''residuals()'' gains ''type'' argument and can compute Pearson residuals
 +  * 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
 +  * added ''ranef.rma.mv()'' for extracting the BLUPs of the random effects for ''rma.mv'' models
 +  * all functions that repeatedly refit models now have the option to show a progress bar
 +  * added ''ranktest.default()'', so user can now pass the outcomes and corresponding sampling variances directly to the function
 +  * added ''regtest.default()'', so user can now pass the outcomes and corresponding sampling variances directly to the function
 +  * ''funnel.default()'' gains ''subset'' argument
 +  * ''funnel.default()'' and ''funnel.rma()'' gain ''col'' and ''bg'' arguments
 +  * ''plot.profile.rma()'' gains ''ylab'' argument
 +  * more consistent handling of ''robust.rma'' objects
 +  * added a print method for ''rma.gosh'' objects
 +  * the (log) relative risk is now called the (log) risk ratio in all help files, plots, code, and comments
 +  * ''escalc()'' can now compute outcome measures based on paired binary data (''"MPRR"'', ''"MPOR"'', ''"MPRD"'', ''"MPORC"'', and ''"MPPETO"'')
 +  * ''escalc()'' can now compute (semi-)partial correlation coefficients (''"PCOR"'', ''"ZPCOR"'', ''"SPCOR"'')
 +  * ''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
 +  * ''escalc()'' can now compute the sampling variance for ''measure="PHI"'' for studies using stratified sampling (''vtpye="ST"'')
 +  * 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
 +  * added ''rbind()'' method for ''escalc'' objects
 +  * added ''as.data.frame()'' method for ''list.rma'' objects
 +  * added a new dataset (''dat.pagliaro1992'') for another illustration of a network meta-analysis
 +  * added a new dataset (''dat.laopaiboon2015'') on the effectiveness of azithromycin for treating lower respiratory tract infections
 +  * ''rma.uni()'' and ''rma.mv()'' now check if the ratio of the largest to smallest sampling variance is very large; results may not be stable then (and very large ratios typically indicate wrongly coded data)
 +  *  model fitting functions now check if extra/superfluous arguments are specified via ''...'' and issues are warning if so
 +  * instead of defining own generic ''ranef()'', import ''ranef()'' from ''nlme''
 +  * improved output formatting
 +  * added more tests (but disabled a few tests on CRAN to avoid some issues when R is compiled with ''%%--%%disable-long-double'')
 +  * some general code cleanup
 +  * renamed ''diagram_metafor.pdf'' vignette to just ''diagram.pdf''
 +  * minor updates in the documentation
  
 ==== Version 1.9-9 (2016-09-25) ==== ==== Version 1.9-9 (2016-09-25) ====
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 ==== Version 1.5-0 (2010-12-16) ==== ==== Version 1.5-0 (2010-12-16) ====
  
-  * the ''metafor'' package now has its own project website at: https://www.metafor-project.org/+  * the ''metafor'' package now has its own project website at: https://www.metafor-project.org
   * added ''labbe()'' function to create L’Abbe plots   * added ''labbe()'' function to create L’Abbe plots
   * the ''forest.default()'' and ''addpoly.default()'' functions now allow the user to directly specify the lower and upper confidence interval bounds (this can be useful when the CI bounds have been calculated with other methods/functions)   * the ''forest.default()'' and ''addpoly.default()'' functions now allow the user to directly specify the lower and upper confidence interval bounds (this can be useful when the CI bounds have been calculated with other methods/functions)
updates_old.txt · Last modified: 2024/03/29 09:56 by Wolfgang Viechtbauer