"The program in Comparative Effectiveness and Outcomes Research at Duke University conducts multiple systematic reviews and meta‐analyses each year for professional organizations as well as under both federal and industry sponsored research initiatives. While we use various programs tailored for specific individual projects including those developed in‐house, we have found Comprehensive Meta‐Analysis (CMA) to be a very facile, adaptable and yet comprehensive package meeting the needs for much of our research and generating publication‐quality graphics. My confidence in the analytic algorithms is buoyed by my knowledge of several of the developers of CMA and based on extensive comparison of results with other algorithms including our own. CMA is also an exceptional educational tool and universally embraced by trainees and young investigators initiating careers in evidence‐based medicine and statistical analysis."

Gary H Lyman, MD, MPH, FRCP (Edin) - Professor of Medicine and Director, Comparative Effectiveness and Outcomes Research, Duke University School of Medicine, and the Duke Comprehensive Cancer Center, Senior Fellow, Duke Center for Clinical Health Policy Research, Durham, NC

"One of the hardest things for non‐statisticians conducting meta‐analyses is to figure out how to combine data when the data are in different forms. Using continuous outcome as an example, one study might report before‐and‐after scores, and another might report change scores. Comprehensive Meta‐Analysis allows one to take data in any form and seamlessly converts it so that all the data can be included, or tells the meta‐analyst what additional information is necessary to complete the process. This one aspect of the program can save hours of time for non‐statisticians who are not used to converting data from one format to another."

Ian Shrier - McGill University, Canada