oneway.test {stats} | R Documentation |
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 |
data |
an optional matrix or data frame (or similar: see
|
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 |
var.equal |
a logical variable indicating whether to treat the
variances in the samples as equal. If |
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. |
data.name |
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.
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))