- metafor: A Meta-Analysis Package for R
- Description: The metafor package is a comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbé, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010).
- Package website: https://www.metafor-project.org
- Package documentation: https://wviechtb.github.io/metafor/
- GitHub repo: https://github.com/wviechtb/metafor
- metadat: Meta-Analysis Datasets for R
- Description: The metadat package is an R data package that contains a large collection of meta-analysis datasets. These datasets are useful for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
- Package documentation: https://wviechtb.github.io/metadat/
- GitHub repo: https://github.com/wviechtb/metadat
- mathjaxr: Using Mathjax in Rd Files
- poolr: Package for Pooling the Results from (Dependent) Tests
- Description: The poolr package contains functions for pooling/combining the results (i.e., p-values) from (dependent) hypothesis tests. Included are Fisher’s method, Stouffer's method, the inverse chi-square method, the Bonferroni method, Tippett's method, and the binomial test. Each method can be adjusted based on an estimate of the effective number of tests or using empirically derived null distribution using pseudo replicates. For Fisher's, Stouffer's, and the inverse chi-square method, direct generalizations based on multivariate theory are also available (leading to Brown's method, Strube's method, and the generalized inverse chi-square method). For an introduction to the package, see Cinar and Viechtbauer (2022).
- Package documentation: https://ozancinar.github.io/poolr/
- GitHub repo: https://github.com/ozancinar/poolr
- esmpack: A Package to Facilitate Preparation and Management of ESM/EMA Data
- Description: The esmpack package is a collection of functions that facilitate preparation, management, visualization, and analysis of data collected via the experience sampling method (ESM) and ecological momentary assessment (EMA).
- Package documentation: https://wviechtb.github.io/esmpack/
- GitHub repo: https://github.com/wviechtb/esmpack
software.txt · Last modified: 2022/09/16 21:56 by Wolfgang Viechtbauer