KWtest

Kruskal-Wallis test for the non parametric analysis of variance.
1,1K download
Aggiornato 30 mar 2018

Kruskal-Wallis test for the non parametric ANOVA
In statistics, the Kruskal–Wallis one-way analysis of variance by ranks (named
after William Kruskal and W. Allen Wallis) is a non-parametric method for
testing equality of population medians among groups. It is identical to a
one-way analysis of variance with the data replaced by their ranks. It is an
extension of the Mann–Whitney U test to 3 or more groups. Since it is a
non-parametric method, the Kruskal–Wallis test does not assume a normal
population, unlike the analogous one-way analysis of variance. However, the
test does assume an identically-shaped and scaled distribution for each group,
except for any difference in medians. The exact distribution of the
Kruskal-Wallis statistics is very time, space and memory expensive, so it is
approximated using other distribution.
The MatLab function KRUSKALWALLIS only uses the chi-square distribution that
is the most conservative (and this means that it accepts the H0 hypothesis more
than you want). This function computes also the F, Beta and Gamma
approximations (the F distribution is the less conservative and this means that
it refuses the H0 more than you want), giving a more informative output (if you
want, see http://www.jmu.edu/assessment/JPM%20AERA%20SP%2008.pdf). If you
believe that the p-value you choose is smaller than your cut-off (usually
0.05), you can use my function Dunn-Sidak to isolate the differences among
groups (http://www.mathworks.com/matlabcentral/fileexchange/12827).
Syntax: STATS=kwtest(X)

Inputs:
X - data matrix (Size of matrix must be n-by-2; data=column 1, group=column 2).

Outputs:
- Statistics of each group (samples, median, sum of ranks and mean rank)
- Correction factor for ties and H statistics
- Chi-square approximation
- F approximation
- Beta approximation
- Gamma approximation
If STATS nargout was specified the results will be stored in the STATS
struct.

To cite this file, this would be an appropriate format:
Cardillo G. (2009). KWTEST: Kruskal-Wallis non parametric test for ANalysis Of VAriance
http://www.mathworks.com/matlabcentral/fileexchange/25860

Cita come

Giuseppe Cardillo (2024). KWtest (https://github.com/dnafinder/kwtest), GitHub. Recuperato .

Compatibilità della release di MATLAB
Creato con R2014b
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Le versioni che utilizzano il ramo predefinito di GitHub non possono essere scaricate

Versione Pubblicato Note della release
2.0.0.0

inputparser, table implementation, github link

1.2.0.0

Changes in description

1.1.0.0

change in help section to cite this function

1.0.0.0

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.