permControl {perm}

Auxiliary for controling permutation tests

Description

A function to create a list of arguments for permTS, permKS or permTREND.

Usage

permControl(cm=NULL,nmc=10^3-1,seed=1234321,digits=12,
    p.conf.level=.99,setSEED=TRUE,tsmethod="central")

Arguments

cm

a choose(n,m) by n matrix, used if method='exact.ce', ignored otherwise

nmc

number of Monte Carlo replications, used if method='exact.mc', ignored otherwise

seed

value used in set.seed if method='exact.mc', ignored otherwise

setSEED

logical, set to FALSE when performing simulations that use method='exact.mc'

p.conf.level

confidence level for p value estimate, used if method='exact.mc', ignored otherwise

digits

number of digits to use in signif for precision of test statistics

tsmethod

method for calculating two-sided p-values, character, either 'central' or 'abs' (see details)

Details

When cm=NULL the resulting matrix is created by chooseMatrix, it may be optionally provided here only so that chooseMatrix does not need to be repeatedly called in simulations. Also when doing simulations with method='exact.mc', use setSEED=FALSE so that the seed is not reset to the same value each time you call the permutation test function.

See calcPvalsMC for description of how p.conf.level is used.

The two-sided method is given by tsmethod. The default 'central' two-sided method is just p=min(1, 2*min(pless,pgreater)), where pless and pgreater are the one-sided p-values. The name 'central' follows the convention of the exact2x2 and exactci packages; so that for example, a two-sample permutation test on a binary response with tsmethod='central' will match the Central Fisher's Exact test (see Fay, 2010). The option tsmethod='abs' defines another method for defining the two-sided p-value. We define it for complete enumeration, but the algorithms may differ. Let Tj be the vector of length N of all possible values of the test statistic under each of N possible permutations. The p-value with tsmethod='abs' is defined as 1/N times the number of times abs(Tj-mean(Tj)) >= abs(T0-mean(Tj)), where T0 is the observed value of the test statistic. This option matches the default two-sided method for the coin package.

Value

An list with the arguments as components.

References

Fay, M.P. (2010). Confidence intervals that match Fisher's exact or Blaker's exact tests. Biostatistics 11(2):373-373.