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Comparison of Two Sample Tests Using Both Relative Efficiency and Power of Test

DOI: 10.4236/ojs.2016.62029, PP. 331-345

Keywords: Asymmetric, Symmetric, Nonparametric Test, Two Sample Tests, Power of Test, Relative Efficiency

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Abstract:

This paper, comparison of two sample tests, is motivated by the fact that in the test of significant difference between two independent samples, numerous methods can be adopted; each may lead to significant different results; this implies that wrong choice of test statistic could lead to erroneous conclusion. To prevent misleading information, there is a need for proper investigation of some selected methods for test of significant difference between variables/subjects most especially, independent samples. The paper examines the efficiency and sensitivity of four test statistics to ascertain which test performs better. Based on the results, the relative efficiency favours median test as being more efficient than modified median test for both symmetric and asymmetric distributions. In terms of power of test, median test is more sensitive than Modified Median (MMED) test since it has higher power irrespective of the sample sizes for both symmetric and asymmetric distribution. In terms of relative efficiency for asymmetric distribution Modified Mann-Whitney U test is more efficient than Mann-Whitney U test (MMWU), and then for symmetric distribution, Mann-Whitney U test (MMWU) is more efficient than Modified Mann-Whitney in sample size of 5; but for other sample sizes considered Modified Mann-Whitney U test (MMWU) is better than Mann-Whitney. Using power of test for both symmetric and asymmetric distributions, Mann-Whitney is more sensitive than Modified Mann-Whitney U test (MMWU) because it has higher power.

References

[1]  Gibbon, J.D. (1992) Nonparametric Statistics: An Introduction. Quantitative Applications in Social Sciences, Sage Publications, New York.
[2]  Afuecheta, E.O., Oyeka, C.A., Ebuh, G.U. and Nnanatu, C.C. (2012) Modified Median Test Intrinsically Adjusted for Ties. Journal of Basic Physical Research, 3, 30-34.
[3]  Mood, A.M. (1954) On the Asymptotic Efficiency of Certain Nonparametric Two-Sample Tests. Annals of Mathematical Statistics, 25, 514-522.
http://dx.doi.org/10.1214/aoms/1177728719
[4]  Siegel, S. (1988) Nonparametric Statistics for the Sciences. McGraw-Hill, Kogakusha Ltd., Tokyo, 399.
[5]  Mann, H.B. and Whitney, D.R. (1947) On a Test of Whether One of Two Random Variables Is Stochastically Larger than the Other. Annals of Mathematical Statistics, 18, 50-60.
http://dx.doi.org/10.1214/aoms/1177730491
[6]  Oyeka, I.C.A. and Okeh, U.M. (2013) Modified Intrinsically Ties Adjusted Mann-Whitney U Test. IOSR Journal of Mathematics, 7, 52-56.
http://dx.doi.org/10.9790/5728-0745256
[7]  Mumby, P.J. (2002) Statistical Power of Non-Parametric Tests: A Quick Guide for Designing Sampling Strategies. Marine Pollution Bulletin, 44, 85-87.
http://www.elsevier.com/locate/marpolbul
http://dx.doi.org/10.1016/S0025-326X(01)00097-2
[8]  Gupta, S.C. (2011) Fundamentals of Statistics. 6th Revised and Enlarged Edition, Himilaza Publishing House PVT Ltd., Mumbai, 16.28-16.31.
[9]  Schaffer, M. (2010) Procedure for Monte Carlo Simulation. SGPE QM Lab 3, Monte Carlos Mark Version of 4.10.2010.

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