Mann-Whitney Test - Definition
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Academic Research on Mann-Whitney Test Mann-Whitney testis not just a test of medians: differences in spread can be important, Hart, A. (2001). Mann-Whitney test is not just a test of medians: differences in spread can be important.BMJ: British Medical Journal,323(7309), 391. This paper explores the use of the Mann-Whitney test. The paper proposes that this test method is mainly used as an alternative to a t test when data are not commonly distributed. It also states the performance capability of the Mann-Whitney test, along with some of its procedures. Different outcomes of the WilcoxonMannWhitney testfrom different statistics packages, Bergmann, R., Ludbrook, J., & Spooren, W. P. (2000). Different outcomes of the WilcoxonMannWhitney test from different statistics packages.The American Statistician,54(1), 72-77. This study of the Mann-Whitney test shows that the variant of the algorithm used for computation by the packages is rarely indicated in the output or documented in the Help facility and the manuals. It concludes that the only accurate form of the WilcoxonMannWhitney procedure is one in which the exact permutation null distribution is compiled for the actual data. Misconceptions leading to choosing the t test over the WilcoxonMann-Whitney testfor shift in location parameter, Sawilowsky, S. S. (2005). Misconceptions leading to choosing the t test over the Wilcoxon Mann-Whitney test for shift in location parameter. This paper studies the common misconceptions in choosing the t test over the Wilcoxon Rank-Sum test when testing for shift. The paper showa that these misconceptions are false statements, true premise but false statements, and true statement irrelevant in choosing between the t test and the Wilcoxon Rank Sum test. The influence of serial correlation on theMannWhitney testfor detecting a shift in median, Yue, S., & Wang, C. (2002). The influence of serial correlation on the MannWhitney test for detecting a shift in median.Advances in Water Resources,25(3), 325-333. This study analyses the non-parametric MannWhitney (MW) statistical test for assessing the significance of a shift in median or mean. It also highlights the different method used by this test when analysing hydrological time series. This study investigates this issue by means of the Monte Carlo simulation. Extension of the Wilcoxon-Mann-Whitney testto samples censored at the same fixed point, Halperin, M. (1960). Extension of the Wilcoxon-Mann-Whitney test to samples censored at the same fixed point.Journal of the American Statistical Association,55(289), 125-138. In this paper, a two-sample non-parametric significance test for censored samples is presented. The null hypothesis considered is that the two samples are from the same population. Wilcoxon-Mann-Whitney testused for data that are not normally distributed, Dexter, F. (2013). Wilcoxon-Mann-Whitney test used for data that are not normally distributed. A semiparametric extension of theMann-Whitney testfor randomly truncated data, Bilker, W. B., & Wang, M. C. (1996). A semiparametric extension of the Mann-Whitney test for randomly truncated data.Biometrics, 10-20. This paper studies the use of the Mann-Whitney test in testing tne equality of two distributions. The paper develops a semiparametric extension for a case when truncation is present. It considers a model in which the truncation distribution is parameterized, while the lifetime distribution is left as a nonparametric component. On neutral responses (zeros) in the sign test and ties in the WilcoxonMannWhitney test, Randles, R. H. (2001). On neutral responses (zeros) in the sign test and ties in the WilcoxonMannWhitney test.The American Statistician,55(2), 96-101. In this paper, an alternative treatment of neutral responses in the sign test is proposed that makes explicit use of the probability of a neutral response in the hypotheses being tested. The extension of this formulation to treating ties in the WilcoxonMannWhitney problem setting is also discussed. Power of theMannWhitney testfor detecting a shift in median or mean of hydro-meteorological data, Yue, S., & Wang, C. Y. (2002). Power of the MannWhitney test for detecting a shift in median or mean of hydro-meteorological data.Stochastic Environmental Research and Risk Assessment,16(4), 307-323. This study investigates the power of the MannWhitney (MW) statistic test in various circumstances by means of Monte Carlo simulation. Simulation results demonstrate that the power of the test is very sensitive to various properties of sample data. Exploiting the link between the Wilcoxon-Mann-Whitney testand a simple odds statistic, OBrien, R. G., & Castelloe, J. (2006, March). Exploiting the link between the Wilcoxon-Mann-Whitney test and a simple odds statistic. InProceedings of the Thirty-first Annual SAS Users Group International Conference. Cary, NC, USA: SAS Institute, USA. http://www2. sas. com/proceedings/sugi31/209-31. pdf (accessed Jan 27, 2008). This paper explores the generational odds ratio (genOR) model of summarizing the association between two ordinal variables, which is generally unknown, and proposes a new statistics model called the WMWodds for properly interpreting and reporting results based on the common Wilcoxon-Mann-Whitney (WMW) two-group test.. A warning about the large-sample Wilcoxon-Mann-Whitney test, Zimmerman, D. W. (2003). A warning about the large-sample Wilcoxon-Mann-Whitney test.Understanding Statistics,2(4), 267-280. This paper advances the notion that the Wilcoxon-Mann-Whitney test is strongly influenced by unequal variances of treatment groups combined with unequal sample sizes. This simulation study indicates that, for various continuous and discrete distributions, the discrepancy between the empirical Type I error rate and the nominal significance level is large even when sample sizes are equal.