The two-sided test of odds-ratio=1 is not necessarily (nor in this case) the same thing as an equal-tailed confidence interval: see the help page comment
Two-sided tests are based on the probabilities of the tables, and take as 'more extreme' all tables with probabilities less than or equal to that of the observed table, the p-value being the sum of such probabilities. > fisher.test(data.50p10min, alternative="greater", conf.level=0.975) Fisher's Exact Test for Count Data data: data.50p10min p-value = 0.02727 alternative hypothesis: true odds ratio is greater than 1 97.5 percent confidence interval: 0.9810441 Inf sample estimates: odds ratio 3.138456 which is not significant at 2.5%, and the two-tailed p-value is not double it. There are other ways to compute confidence intervals, but R's fisher.test() gives the 97.5% lower and upper confidence limits. On Sat, 31 Mar 2007, Williams Scott wrote: > A simple question - using the following fishers test it appears that the P > value is significant, but the CI includes 1. Is this result correct? > > > >> data.50p10min <- matrix(c(16,15, 8, 24),nrow=2) > >> fisher.test(data.50p10min) > > > > Fisher's Exact Test for Count Data > > > > data: data.50p10min > > p-value = 0.03941 > > alternative hypothesis: true odds ratio is not equal to 1 > > 95 percent confidence interval: > > 0.9810441 10.7771597 > > sample estimates: > > odds ratio > > 3.138456 -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.