fligner.test {stats} | R Documentation |

Performs a Fligner-Killeen (median) test of the null that the variances in each of the groups (samples) are the same.

fligner.test(x, ...) ## Default S3 method: fligner.test(x, g, ...) ## S3 method for class 'formula': fligner.test(formula, data, subset, na.action, ...)

`x` |
a numeric vector of data values, or a list of numeric data vectors. |

`g` |
a vector or factor object giving the group for the
corresponding elements of `x` .
Ignored if `x` is a list. |

`formula` |
a formula of the form `lhs ~ rhs` where `lhs`
gives the data values and `rhs` 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. |

If `x`

is a list, its elements are taken as the samples to be
compared for homogeneity of variances, and hence have to be numeric
data vectors. In this case, `g`

is ignored, and one can simply
use `fligner.test(x)`

to perform the test. If the samples are
not yet contained in a list, use `fligner.test(list(x, ...))`

.

Otherwise, `x`

must be a numeric data vector, and `g`

must
be a vector or factor object of the same length as `x`

giving the
group for the corresponding elements of `x`

.

The Fligner-Killeen (median) test has been determined in a simulation
study as one of the many tests for homogeneity of variances which is
most robust against departures from normality, see Conover, Johnson &
Johnson (1981). It is a *k*-sample simple linear rank which uses
the ranks of the absolute values of the centered samples and weights
*a(i) = qnorm((1 +
i/(n+1))/2)*. The version implemented here uses median centering in
each of the samples (F-K:med *X^2* in the reference).

A list of class `"htest"`

containing the following components:

`statistic` |
the Fligner-Killeen:med X^2 test statistic. |

`parameter` |
the degrees of freedom of the approximate chi-squared distribution of the test statistic. |

`p.value` |
the p-value of the test. |

`method` |
the character string
`"Fligner-Killeen test of homogeneity of variances"` . |

`data.name` |
a character string giving the names of the data. |

William J. Conover & Mark E. Johnson & Myrle M. Johnson (1981).
A comparative study of tests for homogeneity of variances, with
applications to the outer continental shelf bidding data.
*Technometrics* **23**, 351–361.

`ansari.test`

and `mood.test`

for rank-based
two-sample test for a difference in scale parameters;
`var.test`

and `bartlett.test`

for parametric
tests for the homogeneity of variances.

plot(count ~ spray, data = InsectSprays) fligner.test(InsectSprays$count, InsectSprays$spray) fligner.test(count ~ spray, data = InsectSprays) ## Compare this to bartlett.test()

[Package *stats* version 2.5.0 Index]