Teaching information for CMA

If you are interested in using CMA to teach a class in meta-analysis, please submit your e-mail here for more information.

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"Comprehensive Meta‐Analysis is a fabulous program for research synthesis, combining ease of use with advanced features not available in standard statistical packages or competing stand‐alone products. The program is ideal for independent analysis or reanalyzing data from another published review (including Cochrane reviews) to explore subgroups, moderator variables, and clinically relevant measures of effect size. Forest and funnel plots can be easily created and customized for publicationquality graphics. As editor in chief of Otolaryngology – Head and Neck Surgery, I find the program indispensable for preparing a quarterly installment, The Cochrane Corner, which highlights a relevant Cochrane review and provides expert commentary to aid clinicians in applying and understanding the results. I strongly recommend this program to novice and experienced meta‐analysts alike."

Richard M. Rosenfeld, MD, MPH - Professor and Chairman of Otolaryngology, SUNY Downstate Medical Center, Brooklyn, NY, Journal Editor and Chair, Guideline Development Task Force, American Academy of Otolaryngology – Head and Neck Surgery


"The program is a perfect companion to Borenstein et al's book since it allowed my students to try the concepts discussed in the book. We have done most of the computations by hand first and then checked our answers with CMA. This gave the students 'a feel' for meta‐analysis and made them realise that the method is not just about feeding some abstract numbers into a black box and getting a meaningless number at the end. Instead, using the book and the program together the students learned the maths behind the computations and the meaning of the final results. I found the help manual especially user‐friendly and ready for classroom use. My students were able to get most of the exercises done at home such that we had the time to discuss the answers and their implications in class."

Dr. Karina De Santis (PhD) - Lecturer in Statistics and Research Methods, Jacobs University, Bremen gGmbH School of Humanities and Social Sciences, Bremen, Germany