mood.test(x, ...)## S3 method for class 'default':
mood.test(x, y,
alternative = c("two.sided", "less", "greater"), ...)
## S3 method for class 'formula':
mood.test(formula, data, subset, na.action, \dots)
"two.sided"
(default), "greater"
or
"less"
all of which can be abbreviated.lhs ~ rhs
where lhs
is a numeric variable giving the data values and rhs
a factor
with two levels giving the corresponding groups.model.frame
) containing the variables in the
formula formula
. By default the variables are taken from
environment(formula)
.NA
s. Defaults to
getOption("na.action")
."htest"
containing the following components:"Mood two-sample test of scale"
.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.
Paul W. Mielke, Jr. (1967), Note on some squared rank tests with existing ties. Technometrics, 9/2, 312--314.
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)
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