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http://dx.doi.org/10.9708/jksci.2020.25.07.175

Combining Independent Permutation p-Values Associated with Multi-Sample Location Test Data  

Um, Yonghwan (Dept. of Industrial and Management Engineering, Sungkyul University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.7, 2020 , pp. 175-182 More about this Journal
Abstract
Fisher's classical method for combining independent p-values from continuous distributions is widely used but it is known to be inadequate for combining p-values from discrete probability distributions. Instead, the discrete analog of Fisher's classical method is used as an alternative for combining p-values from discrete distributions. In this paper, firstly we obtain p-values from discrete probability distributions associated with multi-sample location test data (Fisher-Pitman test and Kruskall-Wallis test data) by permutation method, and secondly combine the permutaion p-values by the discrete analog of Fisher's classical method. And we finally compare the combined p-values from both the discrete analog of Fisher's classical method and Fisher's classical method.
Keywords
Discrete analog of Fisher's classical method; Combining p-values; Fisher-Pitman test; Kruskall-Wallis test; permutation;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 I. H. Tippett, The methods of statistics, Williams and Norgate, London, 1931.
2 R. A. Fisher, "Statistical methods for research workers", (5th ed.) Edinburgh, Scot.: Oliver & Boyd, 1934.
3 S. A. Stouffer, E. A. Suchman, L. C. DeVinney, S. A. Star, and R. M. William, The American Soldier, Adjustment During Army Life, Princeton Univ. Press, Princeton, 1949.
4 B. Wilkinson, "A Statistical Considerration in Psychological Research", Psychological Bull, 48, 156-158, 1951.   DOI
5 D. Zaykin, L. Zhivotovsky, P. H. Westfall, and B. S. Weir, "Truncated product method for combining p-values", Genetic Epidemiology, 22, 170-185, 2002.   DOI
6 E. S. Edington, "An additive model for combining probability values from independent experiments", Journal of Psychology, 80, 351-363, 1972.   DOI
7 R. J. Simes, "An improved Bonferroni procedure for multiple tests of significance", Biometrics, 73, 751-754, 1986.   DOI
8 E. Pesarin, "Multivariate permutation tests: with applications in biostatistics", Chichester, UK: Wiley, 2001.
9 J. T. Kost and M. P. McDermott, "Combining dependent P-values", Statistics & Probability Letters, 60, 183-190, 2002.   DOI
10 J. Seon and D. Kim, "New Method for Combining P-values in Metha-Analysis", The Korean Journal of Applied Statistics, 26, 5, 797-806, 2013.   DOI
11 P. W. Jr. Mielke, J. E. Johnston and K. J. Berry, "Combining probability value from independent permutation tests: a discrete analog of Fisher's classical method", Psychological Reports, 95, 449-458, 2004.   DOI
12 R. A. Fisher, A design of experiment, Oliver & Boyd, Edinburgh, 1935.
13 W. M. Kincaid, "The combination of tests based on discrete distributions", Journal of the American Statistical Association, 57, 10-19, 1962.   DOI
14 P. W. Jr. Mielke, J. E. Johnston and K. J. Berry, "Comparisons of continuous and discrete methods for combining probability values associated with matched-pairs t-test data", 100, 799-805, 2005.   DOI
15 C. E. Lunneborg, "Analysis by resampling: concepts and applications". Pacific Grove, CA: Duxbury, 2000.
16 Y. H. Um, "Combining independent permutation p Values associated with Mann-Whitney test data", Journal of the Korean Society of Computer and Information, 23, 7, 99-104, 2018.
17 K. J. Berry and P. W. Mielke, "The Fisher-Pitman Permutation Test: An Alternative to the F Test", Psychological Reports, 90, 495-502, 2002.   DOI
18 G. W. Corder, and D. I. Foreman. Nonparametric Statistics for Non-Statisticians. Hoboken: John Wiley & Sons. pp. 99-105, 2009.
19 P. W. Mielke Jr. and K. J. Berry, Permutation methods: a distance function approach. (2nd ed.) New York: Springer-Verlag, 2007.