I am running simulations using fisher's test on 2 x c tables and a very small
p.value from fisher's test (<2.2e-16) is returned as a negative number. Code
follows.
> set.seed(0)
Full_Name: Martha Nason
Version: 2.0.1
OS: Windows XP
Submission from: (NULL) (137.187.154.154)
> nreps.outer <-7
> pvalue.fisher <- rep(NA,nreps.outer)
>
> population1 <- c( rep("A",300),seq(1:100))
>
> population2 <- c( rep("A",100),seq(101:200))
>
>
> for (j in 1:nreps.outer){
+ n1 <- sample(30:100,1) + n2 <- sample(30:100,1) + + group1 <- sample(population1, n1, replace=T) + group2 <- sample(population2, n2, replace=T) + + pvalue.fisher[j] <-
+ + print(c(j,pvalue.fisher[j])) + + } [1] 1.000000e+00 3.581362e-05 [1] 2.0000000 0.1424779 [1] 3.0000000 0.1196600 [1] 4.000000000 0.004222897 [1] 5.000000e+00 3.234016e-07
>
> fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))
Fisher's Exact Test for Count Data
data: table(c(group1, group2), c(rep("group1", n1), rep("group2", n2)))
p-value < 2.2e-16
alternative hypothesis: two.sided
> fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))$p.value
[1] -3.847298e-05
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