# permp

0th

Percentile

##### Exact permutation p-values

Calculates exact p-values for permutation tests with permutations sampled with replacement.

Keywords
htest
##### Usage
permp(x, nperm, n1, n2, total.nperm=NULL)
##### Arguments
x
the number of cases that reach the significance threshold in the permutation test
nperm
the number of permutations performed
n1
sample size of group 1
n2
sample size of group 2
total.nperm
the total number of permutations allowable from the design of the experiment
##### Details

This function can be used for calculating p-values for permutation tests where permutations are sampled with replacement. If the total number of permutations, total.nperm, is not known, it can be calculated by specifying the sample sizes in each group, n1 and n2. Note that this is only for a two group experiment. This function calculates the exact permutation p-value, which is given by: (x+1)/(m+1) - (Integration Term). The integration term uses total.nperm, and is enumerated using Gaussian quadrature. It works for a scalar or vector of x's.

##### Value

• permp outputs either a single p-value or a vector of p-values depending on the input

• permp
##### Examples
#  Consider a permutation test with 99 permutations,
#  5 reaching the statistically significant threshold.
#  Assume a two group experiment with 6 in each group.
#  Input total.nperm=462

permp(x=5, nperm=99, total.nperm=462)

# Input n1=6 and n2=6

permp(x=5, nperm=99, n1=6, n2=6)

# Suppose we have a vector of p-values taking on the values 0 to 10 for the same experiment described above.

x<-0:10
permp(x=x, nperm=99, total.nperm=462)
Documentation reproduced from package statmod, version 1.4.4, License: LGPL (>= 2)

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