Quade Test
Description
Performs a Quade test with unreplicated blocked data.
Usage
quade.test(y, ...)
## Default S3 method:
quade.test(y, groups, blocks, ...)
## S3 method for class 'formula'
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 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.
formula
a formula of the form a ~ b | c, where a,
b and c 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
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 NAs. Defaults to
getOption("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 "htest" containing the following components:
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 p-value of the test.
method
the character string "Quade test".
data.name
a character string giving the names of the data.
References
D. Quade (1979), Using weighted rankings in the analysis of complete blocks with additive block effects. Journal of the American Statistical Association 74, 680–683.
William J. Conover (1999), Practical nonparametric statistics. New York: John Wiley & Sons. Pages 373–380.
See Also
Examples
## 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
(qTst <- quade.test(y))
## Show equivalence of different versions of test :
utils::str(dy <- as.data.frame(as.table(y)))
qT. <- quade.test(Freq ~ Brand|Store, data = dy)
qT.$data.name <- qTst$data.name
stopifnot(all.equal(qTst, qT., tolerance = 1e-15))
dys <- dy[order(dy[,"Freq"]),]
qTs <- quade.test(Freq ~ Brand|Store, data = dys)
qTs$data.name <- qTst$data.name
stopifnot(all.equal(qTst, qTs, tolerance = 1e-15))