oneway.test {stats}R Documentation

Test for Equal Means in a One-Way Layout


Test whether two or more samples from normal distributions have the same means. The variances are not necessarily assumed to be equal.


oneway.test(formula, data, subset, na.action, var.equal = FALSE)


formula a formula of the form lhs ~ rhs where lhs gives the sample 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").
var.equal a logical variable indicating whether to treat the variances in the samples as equal. If TRUE, then a simple F test for the equality of means in a one-way analysis of variance is performed. If FALSE, an approximate method of Welch (1951) is used, which generalizes the commonly known 2-sample Welch test to the case of arbitrarily many samples.


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

statistic the value of the test statistic.
parameter the degrees of freedom of the exact or approximate F distribution of the test statistic.
p.value the p-value of the test.
method a character string indicating the test performed. a character string giving the names of the data.


B. L. Welch (1951), On the comparison of several mean values: an alternative approach. Biometrika, 38, 330–336.

See Also

The standard t test (t.test) as the special case for two samples; the Kruskal-Wallis test kruskal.test for a nonparametric test for equal location parameters in a one-way layout.


## Not assuming equal variances
oneway.test(extra ~ group, data = sleep)
## Assuming equal variances
oneway.test(extra ~ group, data = sleep, var.equal = TRUE)
## which gives the same result as
anova(lm(extra ~ group, data = sleep))

[Package stats version 2.5.0 Index]