R: Dunnett's Test for Comparing Several Treatments With a...

DunnettTest {DescTools} | R Documentation

## Dunnett's Test for Comparing Several Treatments With a Control

### Description

Performs Dunnett's test for comparing several treatments with a control.

### Usage

    DunnettTest(x, ...)

    ## Default S3 method:
    DunnettTest(x, g, control = NULL, conf.level = 0.95, ...)

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

### Arguments

`x` | a numeric vector of data values, or a list of numeric data vectors.
`g` | a vector or factor object giving the group for the corresponding elements of `x`. Ignored if `x` is a list.
`control` | the level of the control group against which the others should be tested. If there are multiple levels the calculation will be performed for every one.
`conf.level` | confidence level of the interval.
`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 `NA`s. Defaults to `getOption("na.action")`.
`...` | further arguments to be passed to or from methods.

### Details

`DunnettTest` does the post hoc pairwise multiple comparisons procedure.

If `x` is a list, its elements are taken as the samples to be compared, and hence have to be numeric data vectors. In this case, `g` is ignored, and one can simply use `DunnettTest(x)` to perform the test. If the samples are not yet contained in a list, use `DunnettTest(list(x, ...))`.

Otherwise, `x` must be a numeric data vector, and `g` must be a vector or factor object of the same length as `x` giving the group for the corresponding elements of `x`.

### Value

A list of class `c("PostHocTest")`, containing one matrix named after the control with columns `diff` giving the difference in the observed means, `lwr.ci` giving the lower end point of the interval, `upr.ci` giving the upper end point and `pval` giving the p-value after adjustment for the multiple comparisons.

There are print and plot methods for class `"PostHocTest"`. The plot method does not accept `xlab`, `ylab` or `main` arguments and creates its own values for each plot.

### Author(s)

Andri Signorell <andri@signorell.net>, the interface is based on R-Core code

### References

Dunnett C. W. (1955) A multiple comparison procedure for comparing several treatments with a control, Journal of the American Statistical Association, 50:1096-1121.

### See Also

`PostHocTest`

### Examples

    ## Hollander & Wolfe (1973), 116.
    ## Mucociliary efficiency from the rate of removal of dust in normal
    ##  subjects, subjects with obstructive airway disease, and subjects
    ##  with asbestosis.
    x <- c(2.9, 3.0, 2.5, 2.6, 3.2) # normal subjects
    y <- c(3.8, 2.7, 4.0, 2.4)      # with obstructive airway disease
    z <- c(2.8, 3.4, 3.7, 2.2, 2.0) # with asbestosis

    DunnettTest(list(x, y, z))

    ## Equivalently,
    x <- c(x, y, z)
    g <- factor(rep(1:3, c(5, 4, 5)),
                labels = c("Normal subjects",
                           "Subjects with obstructive airway disease",
                           "Subjects with asbestosis"))

    DunnettTest(x, g)

    ## Formula interface
    boxplot(Ozone ~ Month, data = airquality)
    DunnettTest(Ozone ~ Month, data = airquality)

    DunnettTest(Ozone ~ Month, data = airquality, control="8", conf.level=0.9)

[Package DescTools version 0.99.34 Index]