PMCMRplus (version 1.3.0)

dunnettTest: Dunnett's Many-to-One Comparisons Test

Description

Performs Dunnett's multiple comparisons test with one control.

Usage

dunnettTest(x, ...)
# S3 method for default
dunnettTest(x, g, alternative = c("two.sided", "greater",
  "less"), ...)
# S3 method for formula
dunnettTest(formula, data, subset, na.action,
  alternative = c("two.sided", "greater", "less"), ...)

Arguments

x

a numeric vector of data values, or a list of numeric data vectors.

…

further arguments to be passed to or from methods.

g

a vector or factor object giving the group for the corresponding elements of "x". Ignored with a warning if "x" is a list.

alternative

the alternative hypothesis. Defaults to two.sided.

formula

a formula of the form response ~ group where response gives the data values and group a vector or factor of 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").

Value

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

method

a character string indicating what type of test was performed.

data.name

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

statistic

lower-triangle matrix of the estimated quantiles of the pairwise test statistics.

p.value

lower-triangle matrix of the p-values for the pairwise tests.

alternative

a character string describing the alternative hypothesis.

p.adjust.method

a character string describing the method for p-value adjustment.

model

a data frame of the input data.

dist

a string that denotes the test distribution.

Details

For many-to-one comparisons in an one-factorial layout with normally distributed residuals Dunnett's test can be used. A total of \(m = k-1\) hypotheses can be tested. The null hypothesis H\(_{i}: \mu_0(x) = \mu_i(x)\) is tested in the two-tailed test against the alternative A\(_{i}: \mu_0(x) \ne \mu_i(x), ~~ 1 \le i \le k-1\).

The p-values for the test are calculated from the multivariate t distribution as implemented in the function pmvt.

References

Dunnett, C. W. (1955) A multiple comparison procedure for comparing several treatments with a control. Journal of the American Statistical Association 50, 1096<U+2013>1121.

OECD (ed. 2006) Current approaches in the statistical analysis of ecotoxicity data: A guidance to application - Annexes. OECD Series on testing and assessment, No. 54.

See Also

pmvt

Examples

# NOT RUN {
set.seed(245)
mn <- c(1, 2, 2^2, 2^3, 2^4)
x <- rep(mn, each=5) + rnorm(25)
g <- factor(rep(1:5, each=5))

fit <- aov(x ~ g - 1)
shapiro.test(residuals(fit))
bartlett.test(x ~ g - 1)
anova(fit)
summary(dunnettTest(x, g, alternative = "greater"))

# }