mood.test: Mood Two-Sample Test of Scale

Description

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

Usage

 ```1 2 3 4 5 6 7 8``` ```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. 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.

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.

`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.
 ```1 2 3 4 5 6 7 8``` ```## 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) ```