|
In statistics, the Jonckheere trend test (sometimes called the Jonckheere–Terpstra test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design. It is similar to the Kruskal–Wallis test in that the null hypothesis is that several independent samples are from the same population. However, with the Kruskal–Wallis test there is no a priori ordering of the populations from which the samples are drawn. When there is an ''a priori'' ordering, the Jonckheere test has more statistical power than the Kruskal–Wallis test. The null and alternative hypotheses can be conveniently expressed in terms of population medians for ''k'' populations (where ''k'' > 2). Letting ''θi'' be the population median for the ''i''th population, the null hypothesis is: : The alternative hypothesis is that the population medians have an a priori ordering e.g.: : ≤ ≤ ≤ with at least one strict inequality. ==Procedure== The test can be seen as a special case of Maurice Kendall’s more general method of rank correlation and makes use of the Kendall’s S statistic. This can be computed in one of two ways: 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Jonckheere's trend test」の詳細全文を読む スポンサード リンク
|