| mood.test {stats} | R Documentation |
Performs Mood's two-sample test for a difference in scale parameters.
mood.test(x, ...)
## Default S3 method:
mood.test(x, y,
alternative = c("two.sided", "less", "greater"), ...)
## S3 method for class 'formula'
mood.test(formula, data, subset, na.action, ...)
x, y |
numeric vectors of data values. |
alternative |
indicates the alternative hypothesis and must be
one of |
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 |
... |
further arguments to be passed to or from methods. |
The underlying model is that the two samples are drawn from f(x-l) and f((x-l)/s)/s, respectively, where l is a common location parameter and s is a scale parameter.
The null hypothesis is s = 1.
There are more useful tests for this problem.
In the case of ties, the formulation of Mielke (1967) is employed.
A list with class "htest" containing the following components:
statistic |
the value of the test statistic. |
p.value |
the p-value of the test. |
alternative |
a character string describing the alternative hypothesis. You can specify just the initial letter. |
method |
the character string |
data.name |
a character string giving the names of the data. |
William J. Conover (1971), Practical nonparametric statistics. New York: John Wiley & Sons. Pages 234f.
Paul W. Mielke, Jr. (1967). Note on some squared rank tests with existing ties. Technometrics, 9/2, 312–314. doi: 10.2307/1266427.
fligner.test for a rank-based (nonparametric) k-sample
test for homogeneity of variances;
ansari.test for another rank-based two-sample test for a
difference in scale parameters;
var.test and bartlett.test for parametric
tests for the homogeneity in variance.
## Same data as for the Ansari-Bradley test:
## Serum iron determination using Hyland control sera
ramsay <- c(111, 107, 100, 99, 102, 106, 109, 108, 104, 99,
101, 96, 97, 102, 107, 113, 116, 113, 110, 98)
jung.parekh <- c(107, 108, 106, 98, 105, 103, 110, 105, 104,
100, 96, 108, 103, 104, 114, 114, 113, 108, 106, 99)
mood.test(ramsay, jung.parekh)
## Compare this to ansari.test(ramsay, jung.parekh)