R: Yuen t-Test For Trimmed Means

YuenTTest {DescTools} | R Documentation

## Yuen t-Test For Trimmed Means

### Description

Performs one and two sample Yuen t-tests for trimmed means on vectors of data.

### Usage

    YuenTTest(x, ...)

    ## Default S3 method:
    YuenTTest(x, y = NULL, alternative = c("two.sided", "less", "greater"),
              mu = 0, paired = FALSE, conf.level = 0.95, trim = 0.2, ... )

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

### Arguments

`x` | numeric vector of data values. Non-finite (e.g. infinite or missing) values will be omitted.
`y` | an optional numeric vector of data values: as with x non-finite values will be omitted.
`alternative` | is a character string, one of `"greater"`, `"less"`, or `"two.sided"`, or the initial letter of each, indicating the specification of the alternative hypothesis. For one-sample tests, `alternative` refers to the true median of the parent population in relation to the hypothesized value of the mean.
`paired` | a logical indicating whether you want a paired z-test.
`mu` | a number specifying the hypothesized mean of the population.
`conf.level` | confidence level for the interval computation.
`trim` | the fraction (0 to 0.5) of observations to be trimmed from each end of x before the mean is computed. Values of trim outside that range are taken as the nearest endpoint.
`formula` | a formula of the form `lhs ~ rhs` where `lhs` gives the data values and rhs the corresponding groups.
`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")`.
`...` | further arguments to be passed to or from methods.

### Value

An object of class `htest` containing the following components:

`statistic` | the value of the t-statistic.
`parameter` | the degrees of freedom for the t-statistic and the trim percentage used.
`p.value` | the p-value for the test.
`conf.int` | a confidence interval for the trimmed mean appropriate to the specified alternative hypothesis.
`estimate` | the estimated trimmed mean or difference in trimmed means depending on whether it was a one-sample test or a two-sample test.
`null.value` | the specified hypothesized value of the trimmed mean or trimmed mean difference depending on whether it was a one-sample test or a two-sample test.
`alternative` | a character string describing the alternative hypothesis.
`method` | a character string indicating what type of test was performed.
`data.name` | a character string giving the name(s) of the data.

### Author(s)

Andri Signorell <andri@signorell.net>, based on R-Core code of `t.test`

### References

Wilcox, R. R. (2005) Introduction to robust estimation and hypothesis testing. Academic Press.
Yuen, K. K. (1974) The two-sample trimmed t for unequal population variances. Biometrika, 61, 165-170.

### See Also

`t.test`, `print.htest`

### Examples

    x <- rnorm(25, 100, 5)
    YuenTTest(x, mu=99)

    # the classic interface
    with(sleep, YuenTTest(extra[group == 1], extra[group == 2]))

    # the formula interface
    YuenTTest(extra ~ group, data = sleep)

    # Stahel (2002), pp. 186, 196
    d.tyres <- data.frame(A=c(44.5,55,52.5,50.2,45.3,46.1,52.1,50.5,50.6,49.2),
                          B=c(44.9,54.8,55.6,55.2,55.6,47.7,53,49.1,52.3,50.7))
    with(d.tyres, YuenTTest(A, B, paired=TRUE))

    d.oxen <- data.frame(ext=c(2.7,2.7,1.1,3.0,1.9,3.0,3.8,3.8,0.3,1.9,1.9),
                         int=c(6.5,5.4,8.1,3.5,0.5,3.8,6.8,4.9,9.5,6.2,4.1))
    with(d.oxen, YuenTTest(int, ext, paired=FALSE))

[Package DescTools version 0.99.24 Index]