# p-value¶

pvalue(test::HypothesisTest; tail=:both)

Compute the p-value for a given significance test.

If tail is :both (default), then the p-value for the two-sided test is returned. If tail is :left or :right, then a one-sided test is performed.

## p-value for Fisher exact test¶

function pvalue(x::FisherExactTest; tail=:both, method=:central)

Compute the p-value for a given significance test. The one-sided p-values are based on Fisher’s non-central hypergeometric distribution $$f_\omega(i)$$ with odd-ratio $$\omega$$:

$\begin{split}p_\omega^{(\text{left})} &=\sum_{i\leq a} f_\omega(i)\\ p_\omega^{(\text{right})} &=\sum_{i\geq a} f_\omega(i)\end{split}$

For tail=:both, possible values for method are:

• Central interval :central (default): This p-value is two times the minimum of the one-sided p-values.
• Minimum likelihood interval :minlike: This p-value is computed by summing all tables with the same marginals that are equally or less probable:
$\begin{split}p_\omega &=\sum_{f_\omega(i)\leq f_\omega(a)} f_\omega(i)\end{split}$

Note

Since the p-value is not necessarily unimodal, the corresponding confidence region might not be an interval.

References:

• Gibbons, J.D, Pratt, J.W. P-values: Interpretation and Methodology American Statistican, 29(1):20-25, 1975.
• Fay, M.P. Supplementary material to Confidence intervals that match Fisher’s exact or Blaker’s exact tests. Biostatistics, 0(0):1-13, 2009.