fligner.test {stats}  R Documentation 
Performs a FlignerKilleen (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 
formula 
a formula of the form 
data 
an optional matrix or data frame (or similar: see

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 
... 
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 FlignerKilleen (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 ksample 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 (FK:med X^2 in the reference).
A list of class "htest"
containing the following components:
statistic 
the FlignerKilleen:med X^2 test statistic. 
parameter 
the degrees of freedom of the approximate chisquared distribution of the test statistic. 
p.value 
the pvalue of the test. 
method 
the character string

data.name 
a character string giving the names of the data. 
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.
ansari.test
and mood.test
for rankbased
twosample test for a difference in scale parameters;
var.test
and bartlett.test
for parametric
tests for the homogeneity of variances.
require(graphics) plot(count ~ spray, data = InsectSprays) fligner.test(InsectSprays$count, InsectSprays$spray) fligner.test(count ~ spray, data = InsectSprays) ## Compare this to bartlett.test()