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perm.t.test: Permutational Student's t-test

Description

Performs a permutational Student's t-test.

Usage

perm.t.test(x, ...)

## S3 method for class 'default':
perm.t.test(x, y, paired = FALSE, ...)

## S3 method for class 'formula':
perm.t.test(formula, data, alternative = c("two.sided", "less", "greater"),
  paired = FALSE, nperm = 999, ...)

Arguments

x
a numeric vector of data values.
y
a numeric vector of data values.
paired
a logical indicating whether you want a paired t-test.
formula
a formula of the form a ~ b where a gives the data values and b a factor with 2 levels giving the corresponding groups.
data
an optional data frame containing the variables in the formula formula. By default the variables are taken from environment(formula).
alternative
a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
nperm
number of permutations.
...
further arguments to be passed to or from other methods.

Value

  • statistictest statistics of the parametric test.
  • permutationsnumber of permutations.
  • p.valuep-value of the permutational test.
  • estimatethe estimated mean or difference in means depending on whether it was a paired or not paired test.
  • alternativea character string describing the alternative hypothesis.
  • methoda character string indicating what type of t-test was performed.
  • data.namea character string giving the name(s) of the data.
  • null.valuethe specified hypothesized value of the mean difference, always 0.

Details

The function deals with the limitted floating point precision, which can bias calculation of p-values based on a discrete test statistic distribution.

See Also

t.test

Examples

Run this code
response <- c(rnorm(5),rnorm(5,2,1))
fact <- gl(2,5,labels=LETTERS[1:2])

# Not enough permutations here but faster to run

# Unpaired test
perm.t.test(response~fact,nperm=49)

# Paired test
perm.t.test(response~fact,paired=TRUE,nperm=49)

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