The metafor Package

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Assembling Data for a Meta-Analysis of (Log) Odds Ratios
Assembling Data for a Meta-Analysis of Standardized Mean Differences
Bootstrapping with Meta-Analytic Models
Confidence Intervals for $R^2$ in Meta-Regression Models
Conditional Logistic Regression for Paired Binary Data
Comparison of the Mantel-Haenszel Method in Different Software
Comparing Estimates of Independent Meta-Analyses or Subgroups
Computing Adjusted Effects Based on Meta-Regression Models
Convergence Problems with the rma.mv() Function
Convergence Problems with the rma() Function
Difference Between the Omnibus Test and Tests of Individual Predictors
Allowing $\tau^2$ to Differ Across Subgroups
Forest Plot with Aggregated Values
Forest Plot with Exact Confidence Intervals
Handling Missing Data in Output/Figures
Hunter and Schmidt Method
$\boldsymbol{I^2}$ for Multilevel and Multivariate Models
Increasing Value of $\tau^2$ When Adding Moderators
Specifying Inputs to the rma() Function
Interpreting Coefficients in Meta-Regression Models with (Log) Risk Ratios
Model Selection using the glmulti and MuMIn Packages
Model Selection using the glmulti Package
Meta-Regression Models With or Without an Intercept
Models with Multiple Factors and Their Interaction
Multiple Imputation with the mice and metafor Packages
Modeling Non-Linear Associations in Meta-Regression
Linear Regression and the Mixed-Effects Meta-Regression Model
A Comparison of the rma() and the lm() and lme() Functions
A Comparison of the rma() and the lm(), lme(), and lmer() Functions
A Comparison of the rma.uni() and rma.mv() Functions
Speeding Up Model Fitting
Testing Factors and Linear Combinations of Parameters
Two-Stage Analysis versus Linear Mixed-Effects Models for Longitudinal Data
Weights in Models Fitted with the rma.mv() Function
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