# fligner.test

##### Fligner-Killeen Test of Homogeneity of Variances

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

- Keywords
- htest

##### Usage

`fligner.test(x, …)`# S3 method for default
fligner.test(x, g, …)

# S3 method for formula
fligner.test(formula, data, subset, na.action, …)

##### Arguments

- 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.

##### Details

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 \(a(i) = \mathrm{qnorm}((1 + i/(n+1))/2)\). The version implemented here uses median centering in each of the samples (F-K:med \(X^2\) in the reference).

##### Value

A list of class `"htest"`

containing the following components:

the Fligner-Killeen:med \(X^2\) test statistic.

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

the p-value of the test.

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

.

a character string giving the names of the data.

##### References

William J. Conover, Mark E. Johnson and 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.
10.2307/1268225.

##### See Also

`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.

##### Examples

`library(stats)`

```
# NOT RUN {
require(graphics)
plot(count ~ spray, data = InsectSprays)
fligner.test(InsectSprays$count, InsectSprays$spray)
fligner.test(count ~ spray, data = InsectSprays)
## Compare this to bartlett.test()
# }
```

*Documentation reproduced from package stats, version 3.6.0, License: Part of R 3.6.0*