New Nonparametric Rank-Based Tests for Paired Data
- 1 Department of Environmental and Occupational Health, Epidemiology and Biostatistics Program, University of Nevada Las Vegas, Las Vegas, NV, USA
Abstract
We propose a new nonparametric test based on the rank difference between the paired sample for testing the equality of the marginal distributions from a bivariate distribution. We also consider a modification of the novel nonparametric test based on the test proposed by Baumgartern, Weiβ, and Schindler (1998). An extensive numerical power comparison for various parametric and nonparametric tests was conducted under a wide range of bivariate distributions for small sample sizes. The two new nonparametric tests have comparable power to the paired t test for the data simulated from bivariate normal distributions, and are generally more powerful than the paired t test and other commonly used nonparametric tests in several important bivariate distributions.
- Shapiro, S.S. and Wilk, M.B. (1965) An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52, 591-611. http://dx.doi.org/10.2307/2333709
- Shan, G.G., Vexler, A., Wilding, G. and Hutson, A. (2011) Simple and Exact Empirical Likelihood Ratio Tests for Normality Based on Moment Relations. Communications in Statistics: Simulation and Computation, 40, 129-146. http://dx.doi.org/10.1080/03610918.2010.532896
- Wilcoxon, F. (1945) Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1, 80-83. http://dx.doi.org/10.2307/3001968
- 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
- Lam, F.C. and Longnecker, M.T. (1983) A Modified Wilcoxon Rank Sum Test for Paired Data. Biometrika, 70, 510-513. http://dx.doi.org/10.1093/biomet/70.2.510
- Shan, G.G., Ma, C.X., Hutson, A.D. and Wilding, G.E. (2013) Some Tests for Detecting Trends Based on the Modified Baumgartner Weiβ Schindler Statistics. Computational Statistics & Data Analysis, 57, 246-261. http://dx.doi.org/10.1016/j.csda.2012.04.021
- Fay, M.P. and Proschan, M.A. (2010) Wilcoxon-Mann-Whitney or t-Test? On Assumptions for Hypothesis Tests and Multiple Interpretations of Decision Rules. Statistics Surveys, 4, 1-39.
- Baumgartner, W., Weiβ, P. and Schindler, H. (1998) A Nonparametric Test for the General Two-Sample Problem. Biometrics, 54, 1129-1135. http://dx.doi.org/10.2307/2533862
- Neuhäuser, M. (2001) One-Sided Two-Sample and Trend Tests Based on a Modified Baumgartner-Weiβ Schindler Statistic. Journal of Nonparametric Statistics, 13, 729-739. http://dx.doi.org/10.1080/10485250108832874
- Murakami, H. (2006) A k-Sample Rank Test Based on Modified Baumgartner Statistic and Its Power Comparison. Journal of the Japanese Society of Computational Statistics, 19, 1-13. http://dx.doi.org/10.5183/jjscs1988.19.1
- Kundu, D. and Gupta, R.D. (2009) Bivariate Generalized Exponential Distribution. Journal of Multivariate Analysis, 100, 581-593. http://dx.doi.org/10.1016/j.jmva.2008.06.012
- Antonisamy, B., Christopher, S. and Samuelson, P. (2010) Biostatistics: Principles and Practice. McGraw-Hill Education, New York.
- Wilding, G.E., Shan, G. and Hutson, A.D. (2012) Exact Two-Stage Designs for Phase II Activity Trials with Rank-Based Endpoints. Contemporary Clinical Trials, 33, 332-341. http://dx.doi.org/10.1016/j.cct.2011.10.008