quade.test
Quade Test
Performs a Quade test with unreplicated blocked data.
 Keywords
 htest
Usage
quade.test(y, ...)
"quade.test"(y, groups, blocks, ...)
"quade.test"(formula, data, subset, na.action, ...)
Arguments
 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 ify
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 ify
is a matrix. If not a factor object, it is coerced to one.  formula
 a formula of the form
a ~ b  c
, wherea
,b
andc
give the data values and corresponding groups and blocks, respectively.  data
 an optional matrix or data frame (or similar: see
model.frame
) containing the variables in the formulaformula
. By default the variables are taken fromenvironment(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 togetOption("na.action")
.  ...
 further arguments to be passed to or from methods.
Details
quade.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.
Value

A list with class
 statistic
 the value of Quade's F statistic.
 parameter
 a vector with the numerator and denominator degrees of freedom of the approximate F distribution of the test statistic.
 p.value
 the pvalue of the test.
 method
 the character string
"Quade test"
.  data.name
 a character string giving the names of the data.
"htest"
containing the following components:
References
D. Quade (1979), Using weighted rankings in the analysis of complete blocks with additive block effects. Journal of the American Statistical Association 74, 680683.
William J. Conover (1999), Practical nonparametric statistics. New York: John Wiley & Sons. Pages 373380.
See Also
Examples
library(stats)
## Conover (1999, p. 375f):
## Numbers of five brands of a new hand lotion sold in seven stores
## during one week.
y < matrix(c( 5, 4, 7, 10, 12,
1, 3, 1, 0, 2,
16, 12, 22, 22, 35,
5, 4, 3, 5, 4,
10, 9, 7, 13, 10,
19, 18, 28, 37, 58,
10, 7, 6, 8, 7),
nrow = 7, byrow = TRUE,
dimnames =
list(Store = as.character(1:7),
Brand = LETTERS[1:5]))
y
quade.test(y)