Prof Brian Ripley wrote:
On Sun, 30 Oct 2005, P Ehlers wrote:
dih69530 at syd.odn.ne.jp wrote:
Full_Name: foo ba baz Version: R2.2.0 OS: Mac OS X (10.4) Submission from: (NULL) (219.66.32.183) chisq.test(matrix(c(9,10,9,11),2,2)) Chi-square value must be 0, and, P value must be 0 R does over correction when | a d - b c | < n / 2 ，chi-sq must be 0
(Presumably, you mean P-value = 1.) If you don't want the correction, set correct=FALSE. (The results won't differ much.) A better example is chisq.test(matrix(c(9,10,9,10),2,2)) for which R probably should return X-squared = 0.
R is using the correction that almost all the sources I looked at suggest. You can't go around adjusting X^2 for just some values of the data: the claim is that the adjusted statistic has a more accurate chisq distribution under the null. I think at this remove it does not matter what Yates' suggested (although if I were writing a textbook I would find out), especially as the R documentation does not mention Yates.
You're quite right that, for consistency, the correction should be applied even in the silly example I gave. And, of course, one should not be doing a chisquare test on silly examples. Peter Ehlers