# The metafor Package

A Meta-Analysis Package for R

analyses

## Analysis Examples

The metafor package implements various meta-analytic models, methods, and techniques that have been described in the literature. The links below demonstrate how the models, methods, and techniques described in the respective references can be applied via the metafor package. The items are organized by topic (therefore, articles covering multiple topics may be listed multiple times). Alternatively, you can jump to the references at the bottom of the page for the list of articles in alphabetical order.

### Books on Meta-Analysis

The following items correspond to books on meta-analysis. The analyses described in the books are reproduced using the metafor package.

### Multivariate/Multilevel Meta-Analysis Models

Multivariate/multilevel meta-analytic models can be used to 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).

### Meta-Analysis of Odds Ratios with the Conditional Logistic Model

The conditional logistic model (also called hypergeometric-normal model) can be used to meta-analyze odds ratios (obtained from 2×2 table data).

### Meta-Analysis of Odds Ratios with Peto's Method

The article below describes and illustrates Peto's (one-step) method for meta-analyzing (log) odds ratio.

### Meta-Analysis of Incidence Rates and Rate Ratios

The articles below describe the meta-analysis of incidence rates and incidence rate ratios.

### Meta-Analysis of 2×2 Tables and Person-Time Data using the Mantel-Haenszel Method

The use of the Mantel-Haenszel method for meta-analyzing risk differences, risk ratios, and odds ratios (for 2×2 table data) and for meta-analyzing incidence rate differences and incidence rate ratios (for two-group person-time data) is illustrated in the following article.

### Effect Size Measures for Pretest Posttest Control Group Designs

The article below discusses the calculation of effect size measures for pretest posttest control group designs.

### Best Linear Unbiased Predictions

The articles below illustrate/discuss the calculation of best linear unbiased predictions (BLUPs) (also called empirical Bayes estimates).

### Meta-Analysis with Mixture Models

Instead of assuming normally distributed true effects, one can use mixture models to model heterogeneity in the true effects in a more flexible manner.

### Page Tools 