How precise was the measured difference?
The best way of expressing this is the Confidence Interval (CI). Although
measurements of statistical significance with "p values" are important,
they do not give a picture of the data spread like the CI does.
The usual method is to calculate the "95% CI" which simply defines
the range of values into which the true result (eg. RRR) will be found
95% of the time.
It is important to look at the results and especially the lower and upper
confidence limits to see if the results make sense. These limits may indicate
that not enough patients were enrolled in the study.
If the CI is not given, "p values" can be used. The standard deviation
or standard error can also be multiplied by 2 to give an estimate of the
95% CI.
A better, way of presenting the results would be as an Absolute
Risk Reduction (ARR) as it would better reflect the rarity of the outcome.
In this case the AAA = (20 - 15) = 5%
Application to Pollock et al's
thyroxine paper
In this study, there are very large confidence intervals that reflect
the small sample size and make the results suspect.