Teaching information for CMA
"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
"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