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Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations

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  • Krüger, Jens
  • Chlaß, Nadine

Abstract

This Monte-Carlo study investigates sensitivity of the Wilcoxon signed rank test to certain assumption violations in small samples. Emphasis is put on within-sample-dependence, between-sample dependence, and the presence of ties. Our results show that both assumption violations induce severe size distortions and entail power losses. Surprisingly, these consequences do vary substantially with other properties the data may display. Results provided are particularly relevant for experimental settings where ties and within-sample dependence are frequently observed.
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  • Krüger, Jens & Chlaß, Nadine, 2007. "Small Sample Properties of the Wilcoxon Signed Rank Test with Discontinuous and Dependent Observations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 34399, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:34399
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/34399/
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    1. Hisashi Tanizaki, 1997. "Power comparison of non-parametric tests: Small-sample properties from Monte Carlo experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(5), pages 603-632.
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    3. Dennis A. V. Dittrich & Werner Güth & Martin G. Kocher & Paul Pezanis‐Christou, 2012. "Loss Aversion and Learning to Bid," Economica, London School of Economics and Political Science, vol. 79(314), pages 226-257, April.
    4. MacKinnon, James G, 1994. "Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 167-176, April.
    5. Nick Feltovich, 2003. "Nonparametric Tests of Differences in Medians: Comparison of the Wilcoxon–Mann–Whitney and Robust Rank-Order Tests," Experimental Economics, Springer;Economic Science Association, vol. 6(3), pages 273-297, November.
    6. MacKinnon, James G., 1992. "Approximate Asymptotic Distribution Functions for Unit Roots and Cointegration Tests," Queen's Economics Department Working Papers 273255, Queen's University - Department of Economics.
    7. Cragg, John G, 1983. "More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form," Econometrica, Econometric Society, vol. 51(3), pages 751-763, May.
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    Cited by:

    1. Giulioni, Gianfranco & Bucciarelli, Edgardo, 2011. "Agents’ ability to manage information in centralized markets: Comparing two wholesale fish markets," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 34-49.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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