> Hello, > > I'm looking for some guidance with the following problem: > > I've 2 samples A (111 items) and B (10 items) drawn from the same unknown > population. Witihn A I find 9 "positives" and in B 0 positives. I'd like to > know if the 2 samples A and B are different, ie is there a way to find out > whether the number of "positives" is significantly different in A and B? > > I'm currently using prop.test, but unfortunately some of my data contains > less than 5 items in a group (like in the example above), and the test > statistics may not hold:
The statistic is fine, the approximation to its null distribution may be questionable :-) > > > prop.test(c(9,0), c(111,10)) > > 2-sample test for equality of proportions with continuity correction > > data: c(9, 0) out of c(111, 10) > X-squared = 0.0941, df = 1, p-value = 0.759 > alternative hypothesis: two.sided > 95 percent confidence interval: > -0.02420252 0.18636468 > sample estimates: > prop 1 prop 2 > 0.08108108 0.00000000 > > Warning message: > Chi-squared approximation may be incorrect in: prop.test(c(9, 0), c(111, 10)) > > > Do you have suggestions for an alternative test? > you may consider a permutation test for two independent samples: R> library(exactRankTests) R> x = c(rep(1, 9), rep(0, 102)) R> y = rep(0, 10) R> mean(x) [1] 0.08108108 R> mean(y) [1] 0 R> perm.test(y, x, exact = TRUE) 2-sample Permutation Test data: y and x T = 0, p-value = 0.6092 alternative hypothesis: true mu is not equal to 0 Best, Torsten > many thanks for your help, > +kind regards, > > Arne > > ______________________________________________ > [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