A 2-Day Seminar Taught by David Wilson, Ph.D.
To see a sample of the course materials, click here.
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 and behavioral sciences and medicine, as well as several physical sciences, such as ecology. 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.
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 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). To participate in the hands-on exercises, you are strongly encouraged to bring a laptop computer.
Versions 12 through 15 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 attend
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.
LOCATION, Format, and MATERIALS
The class will meet from 9 am to 5 pm each day with a 1-hour lunch break at the Beacon Hotel, 1615 Rhode Island Ave NW, Washington, D.C. 20036.
Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking.
Registration and lodging
The fee of $995.00 includes all seminar materials. The early registration fee of $895.00 is available until September 25.
If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).
Lodging Reservation Instructions
A block of guest rooms has been reserved at the Beacon Hotel, 1615 Rhode Island Ave NW, Washington, D.C., where the seminar takes place, at a special rate of $259 on October 24 and $179 on October 25. In order to make reservations, call 202-296-2100 during business hours or email email@example.com and identify yourself as part of the Statistical Horizons group. For guaranteed rate and availability, you must reserve your room no later than Wednesday, September 25, 2019.
A block of guest rooms has also been reserved at Hotel 1600, 1600 Rhode Island Ave NW, Washington, D.C. at a special rate of $189 per night. This hotel is about a 2-minute walk to the seminar location. In order to make reservations, click here and enter the group code STATISTICALH. Next, click the orange ‘Check Availability’ button on the right to view available rooms. For guaranteed rate and availability, you must reserve your room no later than Thursday, September 26, 2019.
- Logic of meta-analysis
- Scope and problem formulation
- Computing effect sizes
- Coding studies and database structure
- Fixed-effect meta-analysis
- Random-effects meta-analysis
- Categorical moderator analysis
- Regression based moderator analysis
- Creating forest plots
- Robust standard errors for dependent effect sizes
- Assessing publication bias
- Interpretation and reporting of results
“This course is well-designed to accommodate both the experienced meta-analyst as well as the novice. It offers something for everyone interested in learning more about the topic and provides relevant take-aways and materials for conducting either your first or hundredth meta-analysis! Thank you for such an informative and comprehensive course!”
Kelly Reynolds, Northwestern University
“This is a great course – they couldn’t have a better instructor. Wilson is a fun, engaging instructor and the activities really provide a foundation to implement MA and continue to learn more independently.”
Kathleen Rowan, NORC
“I cannot emphasize enough how much I enjoyed this course. Beginners and students with prior experience conducting meta-analyses will both benefit from Dr. Wilson’s exceptional teaching and the hands-on nature of this course.”
Alison Koenka, The Ohio State University
“The course is an easy to follow, particularly hands on approach to learning both basic and more advanced techniques in a short time frame.”
Robert Arrowood, Texas Christian University
“Even though I had some experience with meta-analyses prior to attending this course, it was still helpful in helping me to understand the nuances of performing MAs in different fields, as well as application of various tools that I wasn’t previously aware of.”
Erica Chuang, Population Council
“I really enjoyed the meta-analysis class and feel that I am ready to apply the concepts and analytical skills in my research areas. Thank you!”
Greg Rhee, Yale University
“Thanks for the excellent course!”
Ji Li, University of Oklahoma Health Science Center
“David is a great instructor and makes a potentially tedious topic fun! Very much enjoyed the two-day seminar and highly recommend it to others!”
Feruzan Irani Williams, Texas Tech University
“Great introduction to the issues of meta-analysis. As a senior scholar who publishes empirical data, I enjoyed learning about how meta-analysts use published studies. The course made me realize the importance of presenting all the critical statistics (means, S.D., N, etc.) in published papers.”
Rachel Pruchno, Rowan University
“Great course! I learned a lot.”
Edgar Kausel, Pontificia Universidad Católica de Chile