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Module contents:
Summary statistics for dichotomous outcome data
Learning objectives
Different types of data
Summarising dichotomous data
Comparing two groups
Risk Difference
Number needed to treat
Putting these statistics in words
Choosing an effect measure
Summary
Next module

 

Risk Difference is the risk in the treated group minus the risk in the control group

Risk Difference

As well as comparing risks in relative terms (i.e. risk in one group divided by the risk in the other), we can also compare them in terms of the absolute difference between the two groups (i.e. the risk in one group minus the risk in the other). This we call the risk difference, or absolute risk difference (it means the same thing).

Risk difference is calculated as risk in the experimental group minus risk in the control group. For our example this is:

RD = Risk in antibiotic group - Risk in placebo group
 
= 0.10 - 0.86
 
= -0.76

The risk difference describes the absolute change in risk that is attributable to the experimental intervention. If an experimental intervention has an identical effect to the control, the risk difference will be 0. If it reduces risk, the risk difference will be less than 0; if it increases risk, the risk difference will be bigger than 0. The risk difference cannot be above 1 or below -1. Switching between good and bad outcomes for the risk difference causes a change of sign, from + to - or - to +.

Sometimes it may be useful to present figures for 100 times the RD, or 1000 times the RD, which describe how many people have avoided (or incurred) the event for every 100 or 1000 treated, respectively.

© The Cochrane Collaboration 2002   Next: Number needed to treat