Dichotomous (binary) outcome data arise when the outcome for every participant is one of two possibilities, for example, dead or alive, or clinical improvement or no clinical improvement. This section considers the possible summary statistics when the outcome of interest has such a binary form. The most commonly encountered effect measures used in clinical trials with dichotomous data are:
the risk ratio (RR) (also called the relative risk);
the odds ratio (OR);
the risk difference (RD) (also called the absolute risk reduction); and
the number needed to treat (NNT).
Details of the calculations of the first three of these measures are given in Box 9.2.a. Numbers needed to treat are discussed in detail in Chapter 12 (Section 12.5).
Aside: As events may occasionally be desirable rather than undesirable, it would be preferable to use a more neutral term than risk (such as probability), but for the sake of convention we use the terms risk ratio and risk difference throughout. We also use the term ‘risk ratio’ in preference to ‘relative risk’ for consistency with other terminology. The two are interchangeable and both conveniently abbreviate to ‘RR’. Note also that we have been careful with the use of the words ‘risk’ and ‘rates’. These words are often treated synonymously. However, we have tried to reserve use of the word ‘rate’ for the data type ‘counts and rates’ where it describes the frequency of events in a measured period of time.