A Simulation Study on the Sample Size in the Mann‑Whitney Test in the Case of Pareto Distribution
DOI:
https://doi.org/10.18778/0208-6018.340.02Keywords:
Mann‑Whitney test, sample size, test power, empirical power, Pareto distribution, Noether methodAbstract
In the paper, the problem of determination of the number of observations necessary for the appropriate use of the non‑parametric Mann‑Whitney test in the case of Pareto distribution is presented. Using the method provided by Noether, the sample size is calculated which guarantees that the Mann‑Whitney U test at a given significance level α has the pre‑assumed power 1 –β. The presented method is examined by calculating empirical power in computer simulations. Moreover, different techniques of rounding the estimated sample size to an even integer number are studied. It is important when two equinumerous samples are to be compared.
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References
Bartlett J. E., Kotrlik J. W., Higgins C. C. (2001), Organizational Research: Determining Appropriate Sample Size in Survey Research, “Learning and Performance Journal”, no. 19, pp. 43–50.
Google Scholar
Chander G. N. (2017), Sample size estimation, “The Journal of Indian Prosthodontic Society”, vol. 17(3), pp. 217–218, http://dx.doi.org/10.4103/jips.jips_169_17.
Google Scholar
De Groot M. M. (1981), Optymalne decyzje statystyczne, Państwowe Wydawnictwo Naukowe, Warszawa.
Google Scholar
Dias K. P., Edwards A. S. (2016), Using Statistical Approaches to Model Natural Disasters, “American Journal of Undergraduate Research”, vol. 13, no. 2, pp. 87–104.
Google Scholar
Draxler C., Kubinger K. D. (2018), Power and Sample Size Considerations in Psychometrics, [in:] J. Pilz, D. Rasch, V. B. Melas, K. Moder (eds.), Statistics and Simulation, Springer Proceedings in Mathematics & Statistics 231, http://dx.doi.org/10.1007/978–3–319–76035–3_3.
Google Scholar
Fisz M. (1967), Rachunek prawdopodobieństwa i statystyka matematyczna, Państwowe Wydawnictwo Naukowe, Warszawa.
Google Scholar
Good I. J. (1953), The population frequencies of species and the estimation of population parameters, “Biometrika”, vol. 40, p. 237–264.
Google Scholar
Mann H. B., Whitney D. R. (1947), On a test of whether one of two random variables is stochastically larger than the other, “Annals of Mathematical Statistics”, vol. 18(1), pp. 50–60.
Google Scholar
Martinez W. L., Martinez A. R. (2015), Computational Statistics Handbook with MATLAB, third edition, Computer Science and Data Analysis Series, Chapman & Hall/CRC Press, New York.
Google Scholar
Noether G. E. (1987), Sample size determination for some common nonparametric test, “JASA”, vol. 82, pp. 645–647.
Google Scholar
Papageorgiou S. N. (2018), On the sample size of clinical trials, “Journal of Orthodontics”, vol. 45(3), pp. 210–212, http://dx.doi.org/10.1080/14653125.2018.1501929.
Google Scholar
Pareto V. (1897), Course d’Economie Politique, F. Rouge Editor, Lusanne–Paris.
Google Scholar
Szymańska A. (2011), The influence of sample size on the estimation of net premius and net premius size in civil responsibility car insurance, “Acta Universitatis Lodziensis. Folia Oeconomica”, no. 255, pp. 35–47.
Google Scholar
Taherdoost H. (2017), Determining Sample Size; How to Calculate Survey Sample Size, “International Journal of Economics and Management Systems”, no. 2, pp. 237–239.
Google Scholar