1 Overview. A description of the purpose of the videos (to help the novice use metafor), and an overview of the remaining 14 videos. Slides.
2 Getting Started. How to download and install R, metafor, and a program to read Excel data files into R. Slides.
3 Uploading Data. Creating an Excel file for your data. Moving data from Excel into R so metafor can compute the meta-analysis. Slides. Data.
4 Preliminary Calcuations. Before you can analyze your data, all the effect sizes must be measured in a common (same across studies) metric such as r, d or log(odds). You may have to covert information presented in the report to an effect size. You can do this in Excel or in R. Slides. R_code. Excel file.
5 Preferred Formats. Metafor will accept generic input (any old effect size and its associated variance or standard error). However, if you are working with r, d, or binary data, there are advantages to providing data to metafor in specific formats. Slides. Correlations (Excel). Means (Excel). Binary (Excel)
6 Fixed and Random Summaries with Generic Input. Finding the overall mean effect size for r, d, and binary data with generic input. Slides. R_code. McNatt data (Excel).
7 Fixed and Random Summaries for r and d with Preferred Input. Slides. Data (Excel file).
8 Fixed and Random Summaries for binary data with Preferred Input. Slides. Data (Excel File)
9 Confidence and Prediction Intervals. How to get confidence intervals and prediction intevals from metafor. Higgins' prediction intervals are also described. Slides. R_code. McNatt data.
10 Moderators. How to analyze categorical and continuous moderators (covariates). How to incorporate multiple moderators into a model. Slides. R_code. Excel File McLeod2007.
11 Funnel Plots. Includes trim-and-fill. Slides. R_code.
12 Forest Plots 1. Basic commands for forest plots; default settings. Slides. R_code.
13 Forest Plots 2. Adding labels to forest plots. Slides. R_code.
14 Forest Plots 3. Adding subgroups to forest plots. Slides.
15 Sensitivity Analysis. Several analyses including forest plots sorted by study precision, Egger's regression (funnel plot asymmetry test) examining studentized residuals (with and without moderators), and leave-one-out analysis. Slides. R_code.
R code only. Our server refuses to show files with the extension .R. I have created a repository in GitHub to hold the .R files. The files for these videos have numbers, so that you know that the R code belongs to that module. For example, 10_Mods.R belongs to module 10.
You may also download a handy list of all the R commands used in my meta-analysis course.