Br Med J (Clin Res Ed) 1986;292:746-750 (15 March), doi:10.1136/bmj.292.6522.746
Confidence intervals rather than P values: estimation rather than hypothesis testing.
Overemphasis on hypothesis testing--and the use of P values
to dichotomise significant or non-significant results--has detracted
from more useful approaches to interpreting study results, such
as estimation and confidence intervals. In medical studies investigators
are usually interested in determining the size of difference
of a measured outcome between groups, rather than a simple indication
of whether or not it is statistically significant. Confidence
intervals present a range of values, on the basis of the sample
data, in which the population value for such a difference may
lie. Some methods of calculating confidence intervals for means
and differences between means are given, with similar information
for proportions. The paper also gives suggestions for graphical
display. Confidence intervals, if appropriate to the type of
study, should be used for major findings in both the main text
of a paper and its abstract.

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