A 3-Day Remote Seminar Taught by David Wilson, Ph.D.

Read reviews of this course

To see a sample of the course materials, click here.

This seminar is currently sold out. To be added to the wait list, email

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, the average effect across studies can be estimated as well as an examination of the consistency of the effects. Analyses can also explore potential explanations for inconsistencies in findings, such as theoretically relevant design differences.

Starting October 8, we are offering this seminar as a 3-day synchronous*, remote workshop for the first time. Each day will consist of a 4-hour live lecture held via the free video-conferencing software Zoom. Participants are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if they are unable to attend at the scheduled time.

Each lecture session will conclude with a hands-on exercise reviewing the content covered, to be completed on your own. An additional session will be held Thursday and Friday afternoons as an “office hour”, where participants can review the exercise results with the instructor and ask any questions.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for one week after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

This course will provide hands-on instruction in conducting all aspects of a meta-analysis, including the systematic nature of the study search and retrieval process, systematic coding and data extraction, computation of various effect size types, and the estimation of both fixed and random-effects meta-analysis models. Students will also learn both categorical and regression based moderator analysis and methods for exploring publication selection bias. Finally, reporting and presentation of the results of a meta-analysis will be taught.


This remote seminar is held via Zoom, a free video conferencing application. Instructions for joining a session via Zoom are available here. Before the seminar begins, participants will receive an email with the meeting code and password you must use to join.

This seminar will use Stata for the worked exercises. However, no previous experience with Stata is assumed. Exercises can also be completed in SPSS and R (on request). Versions 12 through 16 of Stata will work for the course examples and exercises.

Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s free 30-day evaluation offer or their 30-day software return policy.

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.  Participants 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

  1. Logic of meta-analysis
  2. Scope and problem formulation
  3. Computing effect sizes
  4. Coding studies and database structure
  5. Fixed effects meta-analysis
  6. Random-effects meta-analysis
  7. Categorical moderator analysis
  8. Regression based moderator analysis
  9. Creating forest plots
  10. Robust standard errors for dependent effect sizes
  11. Assessing publication bias
  12. Interpretation and reporting of results

REviews of Meta-Analysis

“Dr. Wilson’s Meta-Analysis course was informative and well-organized. He did a great job of balancing the content to meet the diverse needs of the group.”
  Jamaal Young, University of Iowa

“The instructor was terrific. Good pace, good humor, very knowledgeable. Interactive but moved things along. Accommodated all levels of ability/interest. Combination of conceptual overview and computational formulas, along with hands-on exercises, was well-balanced. Instructor enthusiastic and energetic. Generous in taking questions from participants from multiple disciplines and fields.”
  Jane Berry, University of Richmond

“I loved the class! It’s a no-nonsense practical application of meta-analysis. I feel like I can leave the seminar and get started on meta-analysis right away.”
  Nicholas Prince, University of Wyoming

“This course was an excellent introduction to meta-analysis. The instructor was knowledgeable, engaging, and organized. The materials, resources, and lab exercises were extremely helpful. This course is probably appropriate for those who are new to meta-analysis, but provides a solid foundation for more advanced meta-analysis as well.”
  Sabrina Kenny, University at Buffalo / New York City Department of Education

“Thank you for the course. I learned what I came for – now, I feel confident to conduct meta-analyses through Excel.”
  Kalin Kolev, Marquette University

“This Meta-Analysis course works well as an introduction to problematics of meta-analysis. David explains very well every step from the beginning. I really appreciate that he took the time to explain the mathematical background behind each formula. I recommend this course to everyone who comes across meta-analysis in their work.”
  Jakub Gazda, Pavol Jozef Safarik University