Teaching information for CMA

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"Comprehensive Meta‐Analysis is, in my view, the best meta‐analysis software on the market and a "must have" for any meta‐analyst. Before I used this software, I was convinced that specialized metaanalysis software was not necessary at all. At that time, I used my own Excel spreadsheets and SPSS to run meta‐analysis. In fact, I only tried CMA because I needed a way to make forest plots. Once I tried it, however, I was sold. I could not believe how user friendly it was and how much it could do. Suddenly not only was meta‐analysis more efficient, but, more importantly, I could run all types of analyses that previously were not available with the software I had been using. I have since used the program to conduct and publish several meta‐analyses. Given how great the program is, I require it when I teach my graduate meta‐analysis seminar. Students always seem surprised when they see how easy it is to use, as this is certainly not the norm in statistical software. Thus, our graduate students seem to greatly value CMA as a key resource for conducting meta‐analysis."

Seth M. Noar, Ph.D. - Professor, Hussman School of Journalism and Media, University of North Carolina at Chapel Hill


"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. This can make the process of a metaanalysis more time consuming that it necessarily has to be. 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. 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. 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. This meant I could delve deeper into my data to see what was really going on. 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."

Natalie Taylor, PhD - Researcher, Health and Social Psychology Group, Institute of Psychological Sciences, University of Leeds, Leeds