jonckheere.test {clinfun} | R Documentation |
Jonckheere-Terpstra test to test for ordered differences among classes
jonckheere.test(x, g, alternative = c("two.sided", "increasing", "decreasing"), nperm=NULL)
x, g |
data and group vector |
alternative |
means are monotonic (two.sided), increasing, or decreasing |
nperm |
number of permutations for the reference distribution. The default is null in which case the permutation p-value is not computed. Recommend that the user set nperm to be 1000 or higher if permutation p-value is desired. |
jonckheere.test is the exact (permutation) version of the Jonckheere-Terpstra test. It uses the statistic
∑_{k<l} ∑_{ij} I(X_{ik} < X_{jl}) + 0.5 I(X_{ik} = X_{jl}),
where i, j are observations in groups k and l respectively. The asymptotic version is equivalent to cor.test(x, g, method="k"). The exact calculation requires that there be no ties and that the sample size is less than 100. When data are tied and sample size is at most 100 permutation p-value is returned.
Jonckheere, A. R. (1954). A distribution-free k-sample test again ordered alternatives. Biometrika 41:133-145.
Terpstra, T. J. (1952). The asymptotic normality and consistency of Kendall's test against trend, when ties are present in one ranking. Indagationes Mathematicae 14:327-333.
set.seed(1234) g <- rep(1:5, rep(10,5)) x <- rnorm(50) jonckheere.test(x+0.3*g, g) x[1:2] <- mean(x[1:2]) # tied data jonckheere.test(x+0.3*g, g) jonckheere.test(x+0.3*g, g, nperm=5000)