perm.paired.loc {wPerm}

Paired-Sample Permutation Test for Difference in Location

Description

Performs a permutation (randomization) test for difference in location based on a paired sample.

Usage

perm.paired.loc(x, y, parameter, variable = NULL,
                alternative = c("two.sided", "less", "greater"),
                R = 9999)

Arguments

x

a numeric vector of data values representing the first components of the pairs.

y

a numeric vector of data values representing the second components of the pairs.

parameter

the location parameter under consideration (e.g., mean, trimmed mean).

variable

an optional character string that gives the name of the variable under consideration.

alternative

a character string specifying the alternative hypothesis; must be one of "two.sided" (default), "less", or "greater".

R

number of replications (default = 9999).

Details

The null hypothesis is that the distributions of the variable on the two populations are identical—"identical".

The possible alternative hypotheses are:

Two tailed ("two.sided"): The distribution of the variable on the first population has either systematically smaller values or systematically larger values than that of the variable on the second population—"shifted".

Left tailed ("less"): The distribution of the variable on the first population has systematically smaller values than that of the variable on the second population—"shifted.left".

Right tailed ("greater"): The distribution of the variable on the first population has systematically larger values than that of the variable on the second population—"shifted.right".

Value

A list with class "perm.paired.loc" containing the following components:

Perm.values

the values of the test statistic obtained from the permutations.

Header

the main title for the output.

Variable

the name of the variable under consideration or NULL.

Pop.1

the first population.

Pop.2

the second population.

n

the sample size.

Statistic

the test statistic.

Observed

the observed value of the test statistic.

Null

the null hypothesis; here, always identical.

Alternative

the alternative hypothesis.

P.value

the P-value or a statement like P < 0.001.

p.value

the P-value.

Author(s)

Neil A. Weiss

Examples

# Ages of a sample of 10 heterosexual spouses.
data("spouse.ages")
str(spouse.ages)
attach(spouse.ages)

# Paired-sample permutation test to decide whether there is a difference
# in location for age distributions of married men and married women,
# using the mean as the location parameter. Variable named "Age".
perm.paired.loc(HUSBAND, WIFE, mean, "Age")

# Paired-sample permutation test to decide whether married men have
# systematically greater ages than married women, using the 10% trimmed
# mean as the location parameter.
tr10.mean <- function(x) mean(x, trim = 0.10)
perm.paired.loc(HUSBAND, WIFE, tr10.mean, alternative = "greater")

detach(spouse.ages)  # clean up.