  It is widely acknowledged that the biomedical literature suffer from a
surfeit of false positive results. Part of the reason for this is the
persistence of the myth that observation of a p value less than 0.05 is
sufficient justification to claim that you've made a discovery.
  It is hopeless to expect users to change their reliance on p values unless
they are offered an alternative way of judging the reliability of their
conclusions. If the alternative method is to have a chance of being adopted
widely, it will have to be easy to understand and to calculate. One such
proposal is based on calculation of false positive risk.
  It is suggested that p values and confidence intervals should continue to be
given, but that they should be supplemented by a single additional number that
conveys the strength of the evidence better than the p value. This number could
be the minimum false positive risk (that calculated on the assumption of a
prior probability of 0.5, the largest value that can be assumed in the absence
of hard prior data). Alternatively one could specify the prior probability that
it would be necessary to believe in order to achieve a false positive risk of,
say, 0.05.
