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 `"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. |

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.

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. |

William J. Conover (1971),
*Practical nonparametric statistics*.
New York: John Wiley & Sons.
Pages 234f.

`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)

[Package *stats* version 2.5.0 Index]