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PMCMR (version 4.0)

jonckheere.test: Jonckheere-Terpstrata test for testing k independent samples against ordered alternatives

Description

Applies the Jonckheere-Terpstrata test.

Usage

jonckheere.test (x, ...)

## S3 method for class 'default': jonckheere.test(x, g, alternative = c("monotonic", "increasing", "decreasing"), ...)

Arguments

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 x. Ignored if x is a list.
alternative
The alternative hypothesis. Defaults to monotonic.
...
further arguments to be passed to or from methods.

Value

  • A list with class "PMCMR"
  • methodThe applied method.
  • data.nameThe name of the data.
  • p.valueThe p-value of the standard normal distribution.
  • statisticThe estimated quantile of the standard normal distribution.
  • alternativeThe alternative hypothesis.

Details

The global H0, the k medians (med) are equal, is tested against the HA: med_1 <= med_2="" <="..." (increasing="" trend;="" one-sided="" test).="" it="" can="" also="" be="" tested="" for="" decreasing="" trend="" (one-sided="" test)="" and="" monotonic="" (two="" sided="" p="">

See the vignette for details.

References

A. R. Jonckheere (1954). A distribution-free k-sample test against ordered alternatives. Biometrica, 41, 133-145.

L. Sachs (1997), Angewandte Statistik. Berlin: Springer.

See Also

kruskal.test

Examples

Run this code
##
## 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")

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