R: Mood Two-Sample Test of Scale

mood.test {stats} | R Documentation

## Mood Two-Sample Test of Scale

### Description

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

### Usage

    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, ...)

### 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 `NA`s. Defaults to `getOption("na.action")`.
`...` | further arguments to be passed to or from methods.

### 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.

### 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.
`method` | the character string `"Mood two-sample test of scale"`.
`data.name` | a character string giving the names of the data.

### 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

    ## 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)

[Package stats version 3.1.2 Index]