statistic-methods
Extraction of the Test Statistic and Linear Statistic
Methods for extraction of the test statistic and linear statistic.
- Keywords
- methods
Usage
# S4 method for IndependenceLinearStatistic
statistic(object, type = c("test", "linear", "centered", "standardized"), …)
# S4 method for IndependenceTestStatistic
statistic(object, type = c("test", "linear", "centered", "standardized"), …)
# S4 method for IndependenceTest
statistic(object, type = c("test", "linear", "centered", "standardized"), …)Arguments
- object
an object from which the test statistic or linear statistic can be extracted.
- type
a character, the type of statistic: either
"test"(default) for the test statistic,"linear"for the unstandardized linear statistic"centered"for the centered linear statistic or"standardized"for the standardized linear statistic.- …
further arguments (currently ignored).
Details
The method statistic extracts the test statistic or the, possibly
multivariate, linear statistic in its unstandardized, centered or
standardized form.
The test statistic (type = "test") is returned by default. The
unstandardized, centered or standardized linear statistic is obtained by
setting type to "linear", "centered" or
"standardized" respectively.
Value
The test statistic or the unstandardized, centered or standardized linear
statistic extracted from object. A numeric vector or matrix.
Examples
# NOT RUN {
## Example data
dta <- data.frame(
y = gl(4, 5),
x = gl(5, 4)
)
## Asymptotic Cochran-Mantel-Haenszel Test
ct <- cmh_test(y ~ x, data = dta)
## Test statistic
statistic(ct)
## The unstandardized linear statistic...
statistic(ct, type = "linear")
## ...is identical to the contingency table
xtabs(~ x + y, data = dta)
## The centered linear statistic...
statistic(ct, type = "centered")
## ...is identical to
statistic(ct, type = "linear") - expectation(ct)
## The standardized linear statistic, illustrating departures from the null
## hypothesis of independence...
statistic(ct, type = "standardized")
## ...is identical to
(statistic(ct, type = "linear") - expectation(ct)) / sqrt(variance(ct))
# }