stats (version 3.4.3)

mood.test: Mood Two-Sample Test of Scale

Description

Performs Mood's two-sample test for a difference in scale parameters.

Usage

mood.test(x, …)
# S3 method for default
mood.test(x, y,
          alternative = c("two.sided", "less", "greater"), …)
# S3 method for formula
mood.test(formula, data, subset, na.action, …)

Arguments

x, y

numeric vectors of data values.

alternative

indicates the alternative hypothesis and must be one of "two.sided" (default), "greater" or "less" all of which can be abbreviated.

formula

a formula of the form lhs ~ rhs where lhs is a numeric variable giving the data values and rhs a factor with two levels giving 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").

…

further arguments to be passed to or from methods.

Value

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 "Mood two-sample test of scale".

data.name

a character string giving the names of the data.

Details

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.

References

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.

See Also

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.

Examples

# NOT RUN {
## 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)
# }