The metafor Package

A Meta-Analysis Package for R

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todo [2021/06/09 14:35] – [Miscellaneous Features and Things To Do] Wolfgang Viechtbauertodo [2021/10/23 22:26] – Wolfgang Viechtbauer
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   * <del>The ''rma.mv()'' function should allow for one (or multiple?) //continuous// ''inner'' variables in ''random = ~ inner | outer'' for modeling random slopes of moderator variables. This is especially relevant for meta-analyses examining 'dose-response' relationships (assuming there are studies examining the responses to more than two levels of a dose/exposure variable).</del> (DONE!)   * <del>The ''rma.mv()'' function should allow for one (or multiple?) //continuous// ''inner'' variables in ''random = ~ inner | outer'' for modeling random slopes of moderator variables. This is especially relevant for meta-analyses examining 'dose-response' relationships (assuming there are studies examining the responses to more than two levels of a dose/exposure variable).</del> (DONE!)
  
-  * Compute SEs of variance components (and covariances/correlations) in ''rma.mv()''. Not that those SEs are really all that useful. <del>Probably more important: Make ''confint()'' work with ''rma.mv'' objects, to provide profile likelihood CIs.</del> (DONE!).+  * <del>Compute SEs of variance components (and covariances/correlations) in ''rma.mv()''. Not that those SEs are really all that useful.</del> (DONE!) <del>Probably more important: Make ''confint()'' work with ''rma.mv'' objects, to provide profile likelihood CIs.</del> (DONE!).
  
   * Also, make ''blup()'' <del>and ''ranef()''</del> work with ''rma.mv'' objects (and ''rma.glmm'' objects?).   * Also, make ''blup()'' <del>and ''ranef()''</del> work with ''rma.mv'' objects (and ''rma.glmm'' objects?).
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   * <del>Maybe add a ''ranef()'' function (with alias ''random.effects()'' as in the [[http://cran.r-project.org/web/packages/nlme/index.html|nlme]] package) to just extract the predicted random effects (i.e., free of the fixed effects).</del> (DONE!)   * <del>Maybe add a ''ranef()'' function (with alias ''random.effects()'' as in the [[http://cran.r-project.org/web/packages/nlme/index.html|nlme]] package) to just extract the predicted random effects (i.e., free of the fixed effects).</del> (DONE!)
  
-  * The ''rma.glmm()'' function currently uses ±1/2 coding for the random effects when ''model="UM.FS"'' (i.e., an unconditional model with fixed study effects). Maybe provide an option that allows for switching to 0/1 coding?+  * <del>The ''rma.glmm()'' function currently uses ±1/2 coding for the random effects when ''model="UM.FS"'' (i.e., an unconditional model with fixed study effects). Maybe provide an option that allows for switching to 0/1 coding?</del> (DONE!)
  
   * <del>Add the difference, ratio, and odds ratio based on //paired// proportions as outcome measures to ''escalc()''.</del> (DONE!)   * <del>Add the difference, ratio, and odds ratio based on //paired// proportions as outcome measures to ''escalc()''.</del> (DONE!)
todo.txt · Last modified: 2022/08/30 07:01 by Wolfgang Viechtbauer