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
yif this is a vector; ignored ifyis a matrix. If not a factor object, it is coerced to one. - blocks
- a vector giving the block for the corresponding elements
of
yif this is a vector; ignored ifyis a matrix. If not a factor object, it is coerced to one. - formula
- a formula of the form
a ~ b | c, wherea,bandcgive 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
NAs. 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 p-value 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, 680--683.
William J. Conover (1999), Practical nonparametric statistics. New York: John Wiley & Sons. Pages 373--380.
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)