R devel - Apr 2005 - negative p-values from fisher's test (PR#7801)

Full_Name: Martha Nason
Version: 2.0.1
OS: Windows XP
Submission from: (NULL) (137.187.154.154)


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)
> 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] <-
fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))$p.value
+ 
+ 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
[1] 6.000000000 0.003240286
[1]  7.000000e+00 -3.847298e-05
> 
>
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

>>>>> mnason  writes:
> Full_Name: Martha Nason
> Version: 2.0.1
> OS: Windows XP
> Submission from: (NULL) (137.187.154.154)
> 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)
>> 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] <-
>
fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))$p.value
> + 
> + print(c(j,pvalue.fisher[j]))
> + 
> + }
> [1] 1.000000e+00 3.581362e-05
> [1] 2.0000000 0.1424779
> [1] 3.0000000 0.1196600
> [1] 4.000000000 0.004222897
> [1] 5.000000e+00 3.234016e-07
> [1] 6.000000000 0.003240286
> [1]  7.000000e+00 -3.847298e-05
>> 
>>
fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))
>         Fisher's Exact Test for Count Data
> data:  table(c(group1, group2), c(rep("group1", n1),
rep("group2", n2)))
> p-value < 2.2e-16
> alternative hypothesis: two.sided 
>>
fisher.test(table(c(group1,group2),c(rep("group1",n1),rep("group2",n2))))$p.value
> [1] -3.847298e-05
Thanks.

This comes from

L300:
    /* Process node with new PASTP */
    if (pastp <= obs3) {
	/* Update pre */
	*pre += (double) ifreq * exp(pastp + drn);

in f2xact which (e.g. by adding

	REprintf("pre: %f %d %f \n", *pre, ifreq, (double) ifreq * exp(pastp
+ drn));

shows that ifreq may have negative values.

Now ifreq comes from ifrq which has

     IFRQ   - Vector of length LDSTP containing the past path
	      frequencies.  					(in/out)

so I am not sure whether we should have negative values here (we migth
be indexing something one off) ...

Does anyone know how the algorithm works in detail?

-k