Differences

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--- features [2021/04/25 20:03] – [Models and Analysis Approaches] Wolfgang Viechtbauer
+++ features [2021/11/05 07:15] – [Calculation of Effect Sizes and Outcome Measures] Wolfgang Viechtbauer
@@ Line 5: / Line 5: @@
 ==== Calculation of Effect Sizes and Outcome Measures ====
-The package allows the user to calculate various effect sizes and outcome measures frequently used in meta-analyses (''escalc()'' function), including:
+The package allows the user to calculate various effect sizes and outcome measures frequently used in meta-analyses (''[[https://wviechtb.github.io/metafor/reference/escalc.html|escalc()]]'' function), including:
   * risk differences, risk ratios, and odds ratios for 2×2 table data,
@@ Line 20: / Line 20: @@
 The package provides a variety of models and analysis approaches, including:
-  * fixed-, random-, and mixed-effects models using the inverse-variance method (''rma()'' function),
+  * equal/fixed/random-effects models using the inverse-variance method (''rma()'' function),
   * the Mantel-Haenszel and Peto's (one-step) method for 2×2 table and two-group person-time data (''rma.mh()'' and ''rma.peto()'' functions),
   * generalized linear (mixed-effects) models (i.e., mixed-effects (conditional) logistic and Poisson regression models) for the analysis of 2×2 table data, two-group person-time data, proportions, and incidence rates (''rma.glmm()'' function),
@@ Line 28: / Line 28: @@
   * spatio-temporal meta-analytic models (''rma.mv()'' function),
   * subgrouping and (mixed-effects) meta-regression analyses,
-  * location-scale models (''rma()'' function),
+  * location-scale models (''rma()'' function using the ''scale'' argument),
   * models with user-defined weights.
@@ Line 64: / Line 64: @@
   * likelihood ratio and Wald-type tests (''anova()'' function),
+  * improved tests/confidence intervals using the Knapp and Hartung method,
   * confidence intervals for heterogeneity statistics (''confint()'' function),
+  * cluster robust inference methods / robust variance estimation (''robust()'' function),
   * permutation tests (''permutest()'' function),
-  * (cluster) robust tests and confidence intervals (''robust()'' function),
   * cumulative meta-analysis (''cumul()'' function),
   * fitted and predicted outcomes (''fitted()'' and ''predict()'' functions),
   * best linear unbiased predictions (''ranef()'' and ''blup()'' functions),
-  * improved tests/confidence intervals using the Knapp and Hartung method,
   * model fit criteria (''logLik()'' and ''deviance()'' functions),
   * information criteria (''AIC()'', ''BIC()'', and ''fitstats()'' functions),
   * simulation of data from a fitted model (''simulate()'' function).
-The package is also compatible with the [[https://cran.r-project.org/package=glmulti|glmulti]] and [[https://cran.r-project.org/package=MuMIn|MuMIn]] packages for model selection and (multi)model inference (see [[tips:model_selection_with_glmulti|here]] for an illustration), the [[https://cran.r-project.org/package=boot|boot]] package for bootstrapping (see [[tips:bootstrapping_with_ma|here]] for an illustration), and the [[https://cran.r-project.org/package=mice|mice]] and [[https://cran.r-project.org/package=Amelia|Amelia]] packages for multiple imputation (see [[tips:multiple_imputation_with_mice_and_metafor|here]] for an illustration).
+The package is also compatible with the [[https://cran.r-project.org/package=glmulti|glmulti]] and [[https://cran.r-project.org/package=MuMIn|MuMIn]] packages for model selection and multimodel inference (see [[tips:model_selection_with_glmulti_and_mumin|here]] for an illustration), the [[https://cran.r-project.org/package=boot|boot]] package for bootstrapping (see [[tips:bootstrapping_with_ma|here]] for an illustration), and the [[https://cran.r-project.org/package=mice|mice]] and [[https://cran.r-project.org/package=Amelia|Amelia]] packages for multiple imputation (see [[tips:multiple_imputation_with_mice_and_metafor|here]] for an illustration).
 ==== Outlier/Influence Diagnostics ====
@@ Line 88: / Line 88: @@
 ==== Datasets ====
-The package also includes over 50 datasets from published meta-analyses that can be used for teaching and illustration purposes.
+The package also includes over 60 datasets from published meta-analyses that can be used for teaching and illustration purposes (now part of the [[https://cran.r-project.org/package=metadat|metadat]] package).
 ==== Notes ====