Statistical analyses of data and making sense of medical data have received much attention in the medical literature, but nevertheless have caused confusion among practitioners. Each researcher provides a different method for comparing treatments. For example, when the end point is binary, such as disease versus no disease, the common measures are odds ratios, relative risk, relative risk reduction, absolute risk reduction, and the number needed to treat. The question faced by the practitioner is then: Which one will help me in choosing the best treatment for my patient?
The purpose of this paper is to illustrate, using examples, how each measure is used, what it means, and what are its advantages and disadvantages.
Some pairs of measures present equivalent information. Furthermore, it is shown that different measures result in different impressions.
It is recommended that researchers report both a relative and an absolute measure and present these with appropriate confidence intervals.