oneway.test
Test for Equal Means in a One-Way Layout
Description
Performs One-way analysis of means test on data.
Usage
oneway.test(formula, data, subset, na.action, var.equal = FALSE)
Arguments
formula |
a formula or an object containing a formula with the numeric response
on the left side
and a single grouping variable on the right side.
|
data |
a data frame to contain the variables named in the formula and
subset arguments. If you do not supply a value for data,
make sure that the variables in the model formula are in the search path.
|
subset |
a vector that specifies which subset of observations to use in
the formula. By default, all observations are included.
|
na.action |
a character string that specifies how missing values(NAs) are handled.
By default, missing values are silently omitted from the analysis.
|
var.equal |
a logical value, indicates whether to assuming equal variances or not.
The default value of FALSE results in Welch's test.
If var.equal = TRUE, a classical one-way anova test is performed.
|
Value
a list of class
"htest", containing the following components:
statistic |
the equal means statistic in a one-way layout, with names attribute "F".
|
parameter |
the degrees of freedom of formula data,
with names attribute c("num df", "denom df").
|
p.value |
the p-value of the test for equal means.
|
method |
a character string giving the name of the method used.
Currently, it is always One-way analysis of means or
One-way analysis of means(not assuming equal variances).
|
data.name |
a character string containing the actual names extracted
from formula.
|
References
Welch, B. L. 1951. On the comparison of several mean values: an alternative approach. Biometrika. Volume 38. 330-336.
See Also
Examples
y <- c(1, 2, 3, 1, 3, 2, 1, 4, 5, 6, NA, 23, 555, 77, 12)
x <- as.factor(c("A", "A", "A", "A", "A", "A", "A", "B", "B", "B",
"C", "C", "C", "D", "D"))
oneway.test(y ~ x)
oneway.test(y ~ x, na.action = na.omit, var.equal = TRUE)
oneway.test(y ~ x, subset = x %in% c("A", "C"))