From: dsimcha@yahoo.com Full_Name: David Simcha Version: 2.9.0 OS: WinXP Submission from: (NULL) (96.234.244.142) > cor.test(c(1,2,3,4,5), c(8,6,7,5,3), method = "kendall") Kendall's rank correlation tau data: c(1, 2, 3, 4, 5) and c(8, 6, 7, 5, 3) T = 1, p-value = 0.08333 alternative hypothesis: true tau is not equal to 0 sample estimates: tau -0.8 > cor.test(c(1,2,3,4,5), c(8,6,7,5,3), method = "kendall", exact = FALSE) Kendall's rank correlation tau data: c(1, 2, 3, 4, 5) and c(8, 6, 7, 5, 3) z = -1.9596, p-value = 0.05004 alternative hypothesis: true tau is not equal to 0 sample estimates: tau -0.8 It appears that R's implementation of Kendall's Tau does not use any type of continuity correction, producing very bad results when exact P-values are not used.

NOTES: where is the evidence for 'very bad results'? A p value of 5% rather than 8% when the inaccurate option was deliberately chosen? Package Kendall, which does use continuity correction, give 0.08641 Option add in 2.10.0

Audit (from Jitterbug): Tue May 26 10:53:01 2009 ripley changed notes Tue May 26 10:53:01 2009 ripley moved from incoming to wishlst-fulfilled