perm.paired.loc: Paired-Sample Permutation Test for Difference in Location
In wPerm: Permutation Tests

Description Usage Arguments Details Value Author(s) Examples

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

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

`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).

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".

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.

Neil A. Weiss

# 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.

'data.frame':	10 obs. of  2 variables:
 $ HUSBAND: int  59 21 33 78 70 33 68 32 54 52
 $ WIFE   : int  53 22 36 74 64 35 67 28 41 44


 RESULTS OF PERMUTATION PAIRED LOCATION TEST
 BASED ON 9999 REPLICATIONS 

    SUMMARY Variable   Pop.1 Pop.2  n Statistic Observed
 STATISTICS      Age HUSBAND  WIFE 10 diff.mean      3.6

 HYPOTHESIS      Null Alternative P.value
       TEST identical     shifted  0.0528




 RESULTS OF PERMUTATION PAIRED LOCATION TEST
 BASED ON 9999 REPLICATIONS 

    SUMMARY   Pop.1 Pop.2  n      Statistic Observed
 STATISTICS HUSBAND  WIFE 10 diff.tr10.mean    4.125

 HYPOTHESIS      Null   Alternative P.value
       TEST identical shifted.right  0.0355