The metafor package provides a comprehensive collection of functions for conducting meta-analyses in R. The package includes functions for calculating various effect size or outcome measures frequently used in meta-analyses (e.g., risk differences, risk ratios, odds ratios, standardized mean differences, Fisher's r-to-z-transformed correlation coefficients) and then allows the user to fit fixed-, random-, and mixed-effects models to these data. By including study-level covariates (‘moderators’) in these models, so-called ‘meta-regression’ analyses can be carried out. For meta-analyses of 2x2 tables, proportions, incidence rates, and incidence rate ratios, 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 (conditional) logistic and Poisson regression models). For non-independent effect sizes or outcomes (e.g., due to correlated sampling errors, correlated true effects or outcomes, or other forms of clustering), the package also provides a function for fitting multilevel/multivariate meta-analytic models.
addpoly
(Package: metafor) :
Add Polygons to Forest Plots
The function addpoly is generic. It can be used to add polygons to a forest plot, for example, to indicate summary estimates for all or subgroups of studies and to indicate fitted/predicted values based on models involving moderators.
The residuals, rstandard, and rstudent functions can be used to compute residuals, corresponding standard errors, and standardized residuals for models fitted with the rma.uni, rma.mh, rma.peto, and rma.mv functions.
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