Agenda  »  Overview

Course description

Meta-Analysis is the process of synthesizing data from multiple studies to yield a more complete understanding of the effect.  It is the core of evidence-based medicine and epidemiology.  The goal of this course is to teach students how to perform a meta-analysis, to interpret the results properly, and to present the results in a manner that is clear and intuitive.  The techniques that we discuss in these workshops are relevant to any field where a meta-analysis might be employed. Participants typically work in such fields as medicine, epidemiology, health sciences, biostatistics, nursing, veterinary medicine, psychology, education, criminal justice, ecology, marketing, among others.

Basic course (20 hours)

In the basic course we explain how to conduct and report the results for a meta-analysis.  In an analysis where the effect size is consistent across studies the goal will be to identify that common effect size and consider the clinical implications of the findings.  In an analysis where the effect size varies across studies the goal will be to identify the mean effect size and also to quantify the variation in effects and consider the clinical implications of this variation: Is it the case that the treatment’s effect varies from moderate to large; or from minor to moderate; or is the treatment helpful in some cases but harmful in others?

Advanced course (20 hours)

In the advanced course we revisit the same datasets we had used in the basic course. Now, rather than simply quantify the heterogeneity in effects, we try to identify factors that may explain that heterogeneity.  Specifically, we use subgroup analysis (analogous to ANOVA) to compare the effect size in different sets of studies.  And we use meta-regression (analogous to multiple regression) to identify the unique impact of any covariates on the effect size.  We also explore other issues in meta-analysis such as publication bias; limitations of the random-effects model; and options for working with a small number of studies.

What We Do Not Cover

A systematic review is a lengthy process that includes formulating a research problem, searching the literature, deciding which studies to include in the synthesis, and then performing the statistical analysis, called the meta-analysis. This workshop focuses only on this last step, the meta-analysis.


"As a professor of statistics, I was unsure whether to take the initial online course in meta-analysis, thinking that it might either be too dense and jargon-filled to be interesting (given Dr. Borenstein’s impressive credentials and knowledge base) or too basic (given that I was already teaching a course). As I finish the series now, however, I am awestruck by the quality of this offering. Dr. Borenstein is quite simply a master teacher, so he offers complex material in a completely comprehensible form, the best of both worlds. I picked up details on the statistics, the use of CMA, and the theory behind the statistics, but I also (hopefully) will model the style and clarity of his teaching style in my own work in the future. I look forward to the intermediate and advanced sessions."

Constance J. Dalenberg, PhD - Alliant International University - Online Workshop

"I truly appreciated the course. It was very clear, but also very thorough. It was also very clear when it comes to fallacies to take into consideration, when you are publishing a meta-analysis. I can really recommend this course to everybody who are working with or plan to work with Meta-Analysis."

Monica Melby-Lervåg - Professor University of Oslo

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