Meta-Analysis - Online Course
A 4-Day Livestream Seminar Taught by
David WilsonTuesday, June 23 —
Friday, June 26, 2026
10:30am-12:30pm (convert to your local time)
1:30pm-3:00pm
How do you make sense of conflicting results across studies? It is common for a finding that is statistically significant in one study to be statistically nonsignificant in another. Does this reflect differences in the design of the studies? Do the effects actually agree in direction and magnitude even if they are different in statistical significance? What if we have 5 such studies, or 50, or 500? It would be surprising if all such studies were in perfect agreement with one another. Thus, we need a method to make sense of the variability in findings across studies.
Meta-analysis is a statistical solution to this problem and has become a widely-used method for synthesizing results across studies in the social, biomedical, and physical sciences. The key to meta-analysis is the effect size: it encodes the direction and magnitude of the finding on a common scale. Using specialized statistical methods, researchers can estimate the average effect across studies and examine the consistency of those effects. Analyses can also explore potential explanations for inconsistencies in findings, such as theoretically relevant design differences.
This course will provide hands-on instruction in conducting all aspects of a meta-analysis. You’ll learn to systematically search for studies to include in a meta-analysis, to code and extract data systematically, to compute effect sizes of various types, and to estimate both fixed and random-effects meta-analysis models. Finally, you will learn how to report and present the results of a meta-analysis.
Starting June 23, this seminar will be presented as a 4-day synchronous, livestream workshop via Zoom. Each day will feature two lecture sessions with hands-on exercises, separated by a 1-hour break. Live attendance is recommended for the best experience. If you can’t join in real time, recordings will be available within 24 hours and accessible for four weeks after the seminar.
Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
ECTS Equivalent Points: 1
Computing
This seminar will use Stata, SPSS, and R for the worked exercises. The course examples will be demonstrated in each. Students may use the program of their choice for the hands-on exercises.
For those using Stata, version 16+ is needed. SPSS users should have access to version 28 or newer. In R, the metafor package will be used. Basic familiarity with Stata, SPSS, or R is highly desirable, but even novice coders should be able to follow the presentation and do the exercises.
If you’d like to take this course but are concerned that you don’t know enough Stata, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s 30-day software return policy.
If you’d like to take the course but are concerned that you don’t know enough R, working through this free one-hour video will get you up to speed. Or, for more resources, you can check out our page on learning R.
This seminar will use Stata, SPSS, and R for the worked exercises. The course examples will be demonstrated in each. Students may use the program of their choice for the hands-on exercises.
For those using Stata, version 16+ is needed. SPSS users should have access to version 28 or newer. In R, the metafor package will be used. Basic familiarity with Stata, SPSS, or R is highly desirable, but even novice coders should be able to follow the presentation and do the exercises.
If you’d like to take this course but are concerned that you don’t know enough Stata, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s 30-day software return policy.
If you’d like to take the course but are concerned that you don’t know enough R, working through this free one-hour video will get you up to speed. Or, for more resources, you can check out our page on learning R.
Who should register?
This course will be helpful for researchers in any field who want to learn how to statistically synthesize results across independent studies using meta-analytic methods. You should have a basic working knowledge of introductory statistics through multiple regression analysis. No knowledge of matrix algebra is required or assumed, but familiarity with standard statistical notation is useful.
This course will be helpful for researchers in any field who want to learn how to statistically synthesize results across independent studies using meta-analytic methods. You should have a basic working knowledge of introductory statistics through multiple regression analysis. No knowledge of matrix algebra is required or assumed, but familiarity with standard statistical notation is useful.
Seminar outline
Day 1
1. Logic of meta-analysis
2. Scope and problem formulation
3. Computing effect sizes
Day 2
4. Coding studies and database structure
5. Fixed effects meta-analysis
6. Random-effects meta-analysis
Day 3
7. Categorical moderator analysis
8. Regression-based moderator analysis
9. Creating forest plots
Day 4
10. Robust standard errors for dependent effect sizes
11. Assessing publication bias
12. Interpretation and reporting of results
Day 1
1. Logic of meta-analysis
2. Scope and problem formulation
3. Computing effect sizes
Day 2
4. Coding studies and database structure
5. Fixed effects meta-analysis
6. Random-effects meta-analysis
Day 3
7. Categorical moderator analysis
8. Regression-based moderator analysis
9. Creating forest plots
Day 4
10. Robust standard errors for dependent effect sizes
11. Assessing publication bias
12. Interpretation and reporting of results
Payment information
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.