The Fisher-Pitman and powers of ranks permutation tests are shown to provide substantial resistance to extreme values when compared with the conventional t test for analyzing matched-pairs experimental designs.
Get full access to this article
View all access options for this article.
References
1.
American Statistical Association. (1999) Ethical guidelines for statistical practice. Alexandria, VA: American Statistical Association.
2.
DemingW. E. (1965) Principles of professional statistical practice. Annals of Mathematical Statistics, 36, 1883–1900.
3.
FeinsteinA. R. (1993) Permutation tests and “statistical significance.”M.D. Computing: Computers in Medical Practice, 10, 28–41.
4.
FisherR. A. (1935) The design of experiments. Edinburgh, Scot.: Oliver & Boyd.
5.
GardenierJ. S.ResnikD. B. (2001) The misuse of statistics: Concepts, tools, and a research agenda. In SteneckN. H.ScheetzM. D. (Eds.), Investigating research integrity: Proceedings of the first ORI Research Conference on Research Integrity. Bethesda, MD: U.S. Department of Health and Human Services.
6.
HaberM. (1990) Comments on “The test of homogeneity for 2 × 2 contingency tables: A review of and some personal opinions on the controversy” by G. Camilli. Psychological Bulletin, 108, 146–149.
7.
HunterM. A.MayR. B. (1993) Some myths concerning parametric and nonparametric tests. Canadian Psychology, 34, 384–389.
8.
MicceriT. (1989) The unicorn, the normal curve, and other improbable creatures. Psychological Bulletin, 105, 156–166.
9.
MielkeP. W.Jr. (1972) Asymptotic behavior of two-sample tests based on powers of ranks for detecting scale and location alternatives. Journal of the American Statistical Association, 67, 850–854.
10.
MielkeP. W.Jr.BerryK. J. (1976) An extended class of matched-pairs tests based on powers of ranks. Psychometrika, 41, 81–100.
11.
MielkeP. W.Jr.BerryK. J. (1982) An extended class of permutation techniques for matched pairs. Communications in Statistics—Theory and Methods, 11, 1197–1207.
12.
MielkeP. W.Jr.BerryK. J. (1983) Asymptotic clarifications, generalizations, and concerns regarding an extended class of matched pairs tests based on powers of ranks. Psychometrika, 48, 483–485.
13.
MielkeP. W.Jr.BerryK. J. (2001) Permutation methods: A distance function approach. New York: Springer-Verlag.
14.
MielkeP. W.Jr.SenP. K. (1981) On asymptotic non-normal null distributions for locally most powerful rank test statistics. Communications in Statistics—Theory and Methods, 10, 1079–1094.
15.
PitmanE. J. G. (1937a) Significance tests which may be applied to samples from any populations. Supplement to the Journal of the Royal Statistical Society, 4, 119–130.
16.
PitmanE. J. G. (1937b) Significance tests which may be applied to samples from any populations: II. The correlation coefficient test. Supplement to the Journal of the Royal Statistical Society, 4, 225–232.
17.
PitmanE. J. G. (1938) Significance tests which may be applied to samples from any populations: III. The analysis of variance test. Biometrika, 29, 322–335.
18.
RellesD. A.RogersW. H. (1977) Statisticians are fairly robust estimators of location. Journal of the American Statistical Association, 72, 107–111.
19.
WilcoxR. R. (1993) Some results on the Tukey-McLaughlin and Yuen methods for trimmed means when distributions are skewed. Biometrical Journal, 36, 259–273.
20.
WilcoxR. R. (1994) A one-way random-effects model for trimmed means. Psychometrika, 59, 289–306.
21.
WilcoxR. R. (2001) Pairwise comparisons of trimmed means for two or more groups. Psychometrika, 66, 343–356.
22.
WilcoxR. R.KeselmanH. J. (2001) Using trimmed means to compare K measures corresponding to two independent groups. Multivariate Behavioral Research, 36, 421–444.
23.
WilcoxR. R.KeselmanH. J. (2002) Power analyses when comparing trimmed means. Journal of Modern Statistical Methods, 1, 24–31. WilcoxonF., (1945) Individual comparisons by ranking methods. Biometrics, 1. 80–83.
