# Why do users of classical statistical procedures continue to use them even though P-values are like a Birmingham screwdriver?

*by Geoff Robinson*

*Institution:*CSIRO

*Date: Tue 31st January 2012*

*Time: 1:00 PM*

*Location: Room 213, Richard Berry Building, University of Melbourne*

*Abstract*: First, I will review the case against P-values and speculate

about why it has been largely ignored. The only novel result is that

for tests between simple hypotheses, any statistical analysis

procedure which is not conservative relative to the likelihood ratio

can be criticised by constructing a relevant betting procedure. This

betting procedure appears to offer a profit margin to a person quoting

Fisher-Neyman-Pearson confidence levels but it has positive

expectation under both hypotheses to the person criticising those

confidence levels.

Following on from the argument that P-values are not a sensible

measure of the strength of evidence for the simple situation of

testing between two simple hypotheses, I will argue that Wald's

sequential probability ratio test should be modified, that tests

between simple null hypotheses and compound alternative hypotheses

should quote a likelihood ratio rather than a P-level as the measure

of statistical significance, and that for pure hypothesis testing

where there is no defined alternative the tail probability should be

divided by an estimate of Mills' ratio before quoting the result as a

measure of statistical significance. Finally, I will discuss

practical consequences of this alternative approach for the

interpretation of two epidemiological trials.

*For More Information:* contact: Mihee Lee. email: miheel@unimelb.edu.au