overlapping (version 2.2)

perm.test: Permutation test on the (non-)overlapping area

Description

Perform a permutation test on the overlapping index.

Usage

perm.test( x, B = 1000, 
          return.distribution = FALSE, ... )

Value

It returns a list containing the following components:

Zobs

the observed values of non-overlapping index, i.e. 1-\(\eta\).

pval

p-values.

Zperm

the permutation distributions.

Arguments

x

a list of numerical vectors to be compared (each vector is an element of the list).

B

integer, number of permutation replicates.

return.distribution

logical, if TRUE it returns the distribution of permuted Z statistics.

...

options, see function overlap for details.

Author

Massimiliano Pastore

Warning

Currently, it only runs the permutation test on two groups at a time. If x contains more than 2 elements, it performs all paired permutation tests.

Details

It performs a permutation test of the null hypothesis that there is no difference between the two distributions, i.e. the overlapping index (\(\eta\)) is one, or the non-overlapping index (\(1-\eta = \zeta\)) is zero.

References

Perugini, A., Calignano, G., Nucci, M., Finos, L., & Pastore, M. (2024, December 30). How do my distributions differ? Significance testing for the Overlapping Index using Permutation Test. tools:::Rd_expr_doi("https://doi.org/10.31219/osf.io/8h4fe")

Examples

set.seed(20150605)
x <- list(X1=rnorm(100), X2=rt(50,8))

## not run: this example take several minutes
## permutation test
# out <- perm.test( x, return.distribution = TRUE )
# out$pval
# plot( density( out$Zperm ) )
# abline( v = out$Zobs ) 

x <- list(X1=rnorm(100), X2=rt(50,8), X3=rchisq(75,3))
# out <- perm.test( x )
# out$pval