Data extraction in meta-analysis
Extracting data for meta-analysis can be very frustrating because authors often don’t report the summary data that you want, that is, the same statistics and the right statistics for the meta-analysis software e.g. mean and standard deviation. There are some great resources for data extraction to help you convert data from what’s reported into what you want, but perhaps randomised trials are better served (for example, by the excellent Cochrane Handbook) than other study designs. There are other resources but they’re scattered around and are sometimes not accessible to all those who may want to carry out meta-analysis, as some methods involve complicated equations.
The aim of this blog is to provide a series of useful tips on data extraction, to shed light on, and raise awareness of the different methods and equations that are available to convert data into what you need for meta-analysis. I’ll also try to demystify the maths by giving worked examples and only offering the derivation of the equations as an optional extra.
About the author:
Dr Kathy Taylor is a medical statistician in Oxford University's Nuffield Department of Primary Care Health Sciences. Kathy teaches data extraction in Meta-analysis. This is a short course that is also available as part of our MSc in Evidence-Based Health Care, MSc in EBHC Medical Statistics, and MSc in EBHC Systematic Reviews.
Follow updates on this blog, related news, and to find out about other examples of statistics being made more broadly accessible on Twitter: @dataextips