Two methods of ranking $K$ samples for rank tests comparing $K$ populations are considered. The first method ranks the $K$ samples jointly; the second ranks the $K$ samples pairwise. These procedures were first suggested by Dunn (1964), and Steel (1960), respectively. It is shown that both ranking procedures are asymptotically equivalent for rank-sum tests satisfying certain nonrestrictive conditions. The problem is formulated in terms of multiple comparisons, but is applicable to other nonparametric procedures based on $K$-sample rank statistics.
Publié le : 1977-11-14
Classification:
Nonparametric statistics,
linear rank tests,
multiple comparisons,
location,
scale,
asymptotic Pitman efficiency,
62G20,
62G10,
62E20
@article{1176343998,
author = {Koziol, James A. and Reid, Nancy},
title = {On the Asymptotic Equivalence of Two Ranking Methods for $K$-Sample Linear Rank Statistics},
journal = {Ann. Statist.},
volume = {5},
number = {1},
year = {1977},
pages = { 1099-1106},
language = {en},
url = {http://dml.mathdoc.fr/item/1176343998}
}
Koziol, James A.; Reid, Nancy. On the Asymptotic Equivalence of Two Ranking Methods for $K$-Sample Linear Rank Statistics. Ann. Statist., Tome 5 (1977) no. 1, pp. 1099-1106. http://gdmltest.u-ga.fr/item/1176343998/