boot_t_test {TOSTER}R Documentation

Bootstrapped t-test

Description

A function for a bootstrap method for Tt-tests.

Usage

boot_t_test(x, ...)

## Default S3 method:
boot_t_test(
  x,
  y = NULL,
  var.equal = FALSE,
  paired = FALSE,
  alternative = c("two.sided", "less", "greater", "equivalence", "minimal.effect"),
  mu = 0,
  alpha = 0.05,
  R = 1999,
  ...
)

## S3 method for class 'formula'
boot_t_test(formula, data, subset, na.action, ...)

Arguments

x

a (non-empty) numeric vector of data values.

...

further arguments to be passed to or from methods.

y

an optional (non-empty) numeric vector of data values.

var.equal

a logical variable indicating whether to treat the two variances as being equal. If TRUE then the pooled variance is used to estimate the variance otherwise the Welch (or Satterthwaite) approximation to the degrees of freedom is used.

paired

a logical indicating whether you want a paired t-test.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater", "less", "equivalence" (TOST), or "minimal.effect" (TOST). You can specify just the initial letter.

mu

a number indicating the true value of the mean for the two tailed test (or difference in means if you are performing a two sample test).

alpha

alpha level (default = 0.05)

R

number of bootstrap replicates

formula

a formula of the form lhs ~ rhs where lhs is a numeric variable giving the data values and rhs either 1 for a one-sample or paired test or a factor with two levels giving the corresponding groups. If lhs is of class "Pair" and rhs is 1, a paired test is done.

data

an optional matrix or data frame (or similar: see model.frame) containing the variables in the formula formula. By default the variables are taken from environment(formula).

subset

an optional vector specifying a subset of observations to be used.

na.action

a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").

Details

For details on the calculations in this function see vignette("robustTOST").

The implemented test(s) corresponds to the proposal of Chapter 16 of Efron and Tibshirani (1994).

For details on the calculations in this function see vignette("robustTOST").

Value

A list with class "htest" containing the following components:

statistic

the value of the t-statistic.

parameter

the degrees of freedom for the t-statistic.

p.value

the p-value for the test.

conf.int

a confidence interval for the mean appropriate to the specified alternative hypothesis.

estimate

the estimated mean or difference in means depending on whether it was a one-sample test or a two-sample test.

null.value

the specified hypothesized value of the mean or mean difference. May be 2 values.

stderr

the standard error of the mean (difference), used as denominator in the t-statistic formula.

alternative

a character string describing the alternative hypothesis.

method

a character string indicating what type of t-test was performed.

data.name

a character string giving the name(s) of the data..

References

Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap. CRC press.

See Also

Other Robust TOST: boot_log_TOST(), boot_t_TOST(), log_TOST(), wilcox_TOST()

Examples

# example code

boot_t_test(extra ~ group, data = sleep)

[Package TOSTER version 0.7.1 Index]