![]() I planned to use another meta‐analysis software package, but learned about CMA one week before the first day of class. I recently taught an introduction to meta‐analysis course to graduate students from diverse disciplines including ecology, kinesiology, economics, forestry, veterinary medicine, family studies, and plant pathology. 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 ![]() CMA is also an exceptional educational tool and universally embraced by trainees and young investigators initiating careers in evidence‐based medicine and statistical analysis. ![]() 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. 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. 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. 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 I strongly recommend this program to novice and experienced meta‐analysts alike. 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. Forest and funnel plots can be easily created and customized for publicationquality graphics. 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. Researcher, Health and Social Psychology Group, Institute of Psychological Sciences, University of Leeds, LeedsĬomprehensive 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. ![]() ![]() For these more sophisticated methods, the programme also reports the information required to compute additional statistics, such as tau squared within and between studies (enabling me to compute the R squared statistic), which are not provided by some other programmes but are commonly reported in published meta‐analyses. This meant I could delve deeper into my data to see what was really going on. Furthermore, even though I had over 50 moderators to assess, CMA made it simple to test each moderator, whilst offering the option to test moderators according to other specific study characteristics. Upon running the analysis, the programme would compute standardised effect sizes for each study (even though I might have used around 10 different types of data entry), as well as an overall effect size. I found one useful and time‐saving aspect of Comprehensive Meta‐Analysis is that it allowed me to enter effect size data from articles in a number of formats. This can make the process of a metaanalysis more time consuming that it necessarily has to be. Given that publications report a wide range of values from analyses (e.g., means and standard deviations, r, F, t values, eta squared, partial eta squared, etc.), it can be extremely difficult to compute effect sizes that take each of these factors into consideration. ![]()
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