Effect Size Calculation
Once you've extracted the necessary information from your primary studies during the systematic review, then you will be able to use metaanalysis methods to apply statistical techniques to the data that has been collected. Typical steps of a metaanalysis include:
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Calculating the effect sizes that match your research question's outcome(s) of interest

Exploring the distribution of effect sizes, including estimating the mean effect size, its standard error and the heterogeneity among effect sizes in your sample

Conducting a metaregression using any relevant moderators to examine heterogeneity in effect sizes

Reporting the results of your metaanalysis, including any subgroup analyses and metaregression modelsâ€‹â€‹â€‹â€‹â€‹â€‹â€‹â€‹â€‹â€‹
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Our metaanalysis Video Guides provide more detailed information on how to calculate the most common effect sizes in education research, how to explore the distribution of effect sizes in your sample (estimating the mean effect size, its standard error and the heterogeneity among effect sizes), conduct metaregression analyses, and conducting metaanalyses using R. For those who are interested in more background in R, those video guides also include an introduction to basic functions in that data analysis software.
Below is a list of the Video Guides:
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Videos for getting started with R
1. Installing R and R Studio
2. Basics of R Studio
3. Importing data into R Studio
4. Transforming data in R
Introduction to the R program metafor (see Wolfgang Viechtbauer's website for more detail info)â€‹
Videos for using escalc in metafor to compute
1. Standardized mean difference
2. Fisher's z transformation of a correlation coefficient
3. Logodds ratio
1. Introduction to Metaanalysisâ€‹
2. Conducting a basic metaanalysis
3. Coding for metaregression
Additionally, our metaanalysis Lecture Videos provide a deep dive into metaanalysis techniques that reflect the multilevel/hierarchical and correlated data structure of effect sizes. Below is a list of the Lectures from the Modern MetaAnalysis Research Institute (MMARI):
1. Data extraction for a metaanalysis
2. Extracting data from studies for an effect size
3. Introduction to metaanalysis using the R program metafor
4. Models for dependent effect sizes in metaanalysis (using metafor and clubSandwich)
5. Describing sources of heterogeneity in metaanalysis
6. Interpreting heterogeneity in a metaanalysis
Using R can facilitate the conduct of a metaanalysis. Several packages are used to conduct a metaanalysis in R. They include but are not limited to:

metafor

robuMeta

clubSandwich

meta

metaSEM

metaForest
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You can visit the RDocumentation page for each package to learn more.