RevMan (or Review Manager) is designed as a review tool to facilitate the literature review and the meta analyses by the Cochrane Collaboration Group. RevMan can be downloaded from website for free. It can be installed into your system without requiring the system administer privilege. Thousands of systematic reviews and meta analyses published on the Cochrane Library are performed using RevMan. These systemic reviews and meta analyses have been one of the leading resources in evidence-based medicine.
RevMan can be easily used by the medical researchers who are non-statisticians. For statisticians who work in the medical research area, RevMan is an easy tool to perform the meta analyses and generate the graphs (forest plot, funnel plot) in publication standard.
The statistical method and statistical model are described in the document Standard statistical algorithms in Cochrane reviews by Jon Deeks and Julian Higgins and Cochrane Handbook for Systemic Review of Interventions. For statistical models, both fixed model and random model are included in the RevMan. For random models, DerSimonian and Laird random-effects models are used. This is most common random effects model used in Meta Analysis.
RevMan 5 is extremely easy to use. Various tutorials, tips, webinars are provided in RevMan documentation website and The Cochrane Collaboration Open Learning Material. I find it is extremely useful to watch two webinars (especially the part 2 regarding the data and analyses. For
To perform a
Meta analysis, RevMan is just a tool. There are a lot of works to be done prior to enter the information including data into the RevMan. Considerable time needs to be spent on the literature search. Since the data used in Meta analyses relies on the publications, some data needs to be converted first. For example, for outcomes measured in continuous variable, the published article may only provide the Standard Error or just the 95% confidence interval. The SE can be easily converted to the Standard Deviation by multiplying the square root of the sample size. If only the 95% confidence interval is available, the standard deviation can be approximated by normal approximation using upper bound = mean +/- 1.96 * SE.