R: Jonckheere-Terpstrata test for testing k independent samples...

jonckheere.test {PMCMR} | R Documentation

## Jonckheere-Terpstrata test for testing k independent samples against ordered alternatives

### Description

Applies the Jonckheere-Terpstrata test.

### Usage

    jonckheere.test (x, ...)

    ## Default S3 method:
     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.

### Details

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.

### Value

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.

### Author(s)

Thorsten Pohlert

### 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

    ##
    ## 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")

[Package PMCMR version 4.2 Index]