Re: Why stats.fisher_exact gives results different from R?

Also:

BUG: stats: fisher_exact returns incorrect p-value
https://github.com/scipy/scipy/issues/4130

- Stu

On Sat, Apr 6, 2019 at 12:37 PM Stuart Reynolds
<[email protected]> wrote:
>
> Also see:
>     https://github.com/brentp/fishers_exact_test/issues/18
> .... it's a **much** faster implementation of fisher's exact, and also
> differs from scipy.stats.fisher_exact.
> I think the brentp implementation is the same as R's -- actually would
> be good to test this and update the issue.
>
> - Stuart
>
>
> On Sat, Apr 6, 2019 at 6:22 AM <[email protected]> wrote:
> >
> > On Sat, Apr 6, 2019 at 9:02 AM Peng Yu <[email protected]> wrote:
> > >
> > > See below for the output of python and R.
> > >
> > > Why there is a difference in the odds ratio? Given that R is most
> > > widely used by statisticians, I'd prefer the python version print the
> > > same results. Also, confidence intervals are missing in the python's
> > > output.
> > >
> > > >>> stats.fisher_exact([[8, 2], [1, 5]])
> > > (20.0, 0.03496503496503495)
> > >
> > > R> fisher.test(rbind(c(8, 2), c(1,5)))
> > >
> > >     Fisher's Exact Test for Count Data
> > >
> > > data:  rbind(c(8, 2), c(1, 5))
> > > p-value = 0.03497
> > > alternative hypothesis: true odds ratio is not equal to 1
> > > 95 percent confidence interval:
> > >     1.008849 1049.791446
> > > sample estimates:
> > > odds ratio
> > >   15.46969
> >
> > estimate
> > an estimate of the odds ratio. Note that the conditional Maximum
> > Likelihood Estimate (MLE) rather than the unconditional MLE (the
> > sample odds ratio) is used. Only present in the 2 by 2 case.
> > https://stat.ethz.ch/R-manual/R-devel/library/stats/html/fisher.test.html
> >
> > scipy shows sample odds ratio
> >
> > The R help page does not show which confidence interval method they
> > use, and I don't remember or never knew.
> >
> > Josef
> >
> > >
> > > --
> > > Regards,
> > > Peng
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