"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

"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