| jonckheere.test {PMCMR} | R Documentation |
Applies the Jonckheere-Terpstrata test.
jonckheere.test (x, ...)
## Default S3 method:
jonckheere.test(x, g, alternative = c("monotonic", "increasing", "decreasing"), ...)
x |
a numeric vector of data values, or a list of numeric data vectors. |
g |
a vector or factor object giving the group for the
corresponding elements of |
alternative |
The alternative hypothesis. Defaults to |
... |
further arguments to be passed to or from methods. |
The global H0, the k medians (med) are equal, is tested against the HA: med_1 <= med_2 <= ... <= med_k (increasing trend; one-sided test). It can also be tested for decreasing trend (one-sided test) and monotonic trend (two sided test).
See the vignette for details.
A list with class "PMCMR"
method |
The applied method. |
data.name |
The name of the data. |
p.value |
The p-value of the standard normal distribution. |
statistic |
The estimated quantile of the standard normal distribution. |
alternative |
The alternative hypothesis. |
Thorsten Pohlert
A. R. Jonckheere (1954). A distribution-free k-sample test against ordered alternatives. Biometrica, 41, 133-145.
L. Sachs (1997), Angewandte Statistik. Berlin: Springer.
##
## Example from Sachs (1997, p. 402)
x <- c(106, 114, 116, 127, 145, 110, 125,
143, 148, 151, 136, 139, 149, 160,
174)
g <- as.factor(c(rep(1,5), rep(2,5), rep(3,5)))
levels(g) <- c("A", "B", "C")
jonckheere.test(x , g, "increasing")