Prof Brian Ripley <[EMAIL PROTECTED]> writes:
>
> AFAIK R does not have a means of doing Fisher's test on such a table, and
> it really does not make much statistical sense to do so. With such
> numbers, the null hypothesis is almost always rejected (try the chisq
> test), even for negligible dependence.
I have to disagree a little here. If the count in the smaller group
had been smaller we would have been well inside the scope of exact
testing, e.g.
> fisher.test(matrix(c(4, 3070, 2868, 4961135), 2),or=1+1e-15)
Fisher's Exact Test for Count Data
data: matrix(c(4, 3070, 2868, 4961135), 2)
p-value = 0.105
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.6132965 5.7830438
sample estimates:
odds ratio
2.253824
(And the workspace issue still applies, hence the or= fiddle)
A professional statistician would know enough to switch to the
binomial (or Poisson) approximation, but others might need help.
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
