friedman.test(y, groups, blocks)
y
| either a numeric vector of data values, or a data matrix. |
groups
|
a vector giving the group for the corresponding elements
of y if this is a vector; ignored if y is a matrix.
If not a factor object, it is coerced to one.
|
blocks
|
a vector giving the block for the corresponding elements
of y if this is a vector; ignored if y is a matrix.
If not a factor object, it is coerced to one.
|
friedman.test can be used for analyzing unreplicated complete
block designs (i.e., there is exactly one observation in y for
each combination of levels of groups and blocks) where
the normality assumption may be violated.
The null hypothesis is that apart from an effect of blocks, the
location parameter of y is the same in each of the
groups.
If y is a matrix, groups and blocks are obtained
from the column and row indices, respectively. NA's are not
allowed in groups or blocks; if y contains
NA's, corresponding blocks are removed.
"htest" containing the following components:
statistic
| the value of Friedman's chi-square statistic. |
parameter
| the degrees of freedom of the approximate chi-square distribution of the test statistic. |
p.value
| the p-value of the test. |
method
|
the string "Friedman rank sum test".
|
data.name
| a character string giving the names of the data. |