On 7 Nov 2003 at 8:19, Thomas Lumley wrote: Just to make the point more clear:
> fisher.test( matrix(c(42,0,0,0),2,2)) Fisher's Exact Test for Count Data data: matrix(c(42, 0, 0, 0), 2, 2) p-value = 1 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 0 Inf sample estimates: odds ratio 0 The confidence interval for odds ratio goes from 0 to infinity, a rather clear way of saying there is no information. Kjetil Halvorsen > On Fri, 7 Nov 2003, Christoph Bier wrote: > > > Peter Dalgaard wrote: > > > > > Well, the error message might be slightly beside the point, but the > > > issue would seem to be that there are no "ja"'s inside either vector. > > > I.e. it first reduces each factor to those levels that are actually > > > present, then checks whether there are at least two levels. > > > > Thanks for this explanation. > > > > > You can't do a chisquare test on a table that looks like this > > > > > > nein ja > > > nein 42 0 > > > ja 0 0 > > > > > > > Hm, and now? There is data like this and I need to do a chisquare > > test. Spencer's answer seems to be the solution. > > Is my data that uncommon, that chisq.test hasn't a built-in > > function to avoid this error? > > > > It's not that your data are uncommon. Your data contain no information > about whether `ja' answers tend to occur together for the two variables, > because there no `ja' answers. > > -thomas > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help