Number, mean and standard deviation of the outcome for each group Ln(x) and its standard error, where ln is the natural log and x is odds ratio, relative risk or hazard ratio Number and number with the outcome in each group Numbers of true positives, true negatives, false positives and false negatives of the diagnostic test The data that you will be looking to extract, to input into meta-analysis software, will depend on the outcome and these data will typically be: I’ll also try to demystify the maths by giving worked examples and only offering the derivation of the equations as an optional extra. The aim of this resource 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. 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. 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. 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.
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