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Four-decision tests for stochastic dominance, with an application to environmental psychophysics
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0003-1205-3073
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.ORCID iD: 0000-0002-7886-0911
Department of Forest Economics, Swedish University of Agricultural Sciences, Umeå, Sweden.
Gösta Ekman Laboratory, Department of Psychology, Stockholm University, Stockholm, Sweden.
2019 (English)In: Journal of mathematical psychology (Print), ISSN 0022-2496, E-ISSN 1096-0880, Vol. 93, article id 102281Article in journal (Refereed) Published
Abstract [en]

If the survival function of a random variable X lies to the right of the survival function of a random variable Y, then X is said to stochastically dominate Y. Inferring stochastic dominance is particularly complicated because comparing survival functions raises four possible hypotheses: identical survival functions, dominance of X over Y, dominance of Y over X, or crossing survival functions. In this paper, we suggest four-decision tests for stochastic dominance suitable for paired samples. The tests are permutation-based and do not rely on distributional assumptions. One-sided Cramér–von Mises and Kolmogorov–Smirnov statistics are employed but the general idea may be utilized with other test statistics. The power to detect dominance and the different types of wrong decisions are investigated in an extensive simulation study. The proposed tests are applied to data from an experiment concerning the individual’s willingness to pay for a given environmental improvement.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 93, article id 102281
Keywords [en]
Stochastic dominance, Stochastic ordering, Four-hypothesis test, Permutation test, Nonparametric approach, Environmental psychology
National Category
Probability Theory and Statistics Psychology Social Sciences Interdisciplinary
Research subject
Statistics; Psychology
Identifiers
URN: urn:nbn:se:umu:diva-164293DOI: 10.1016/j.jmp.2019.102281ISI: 000501403100004Scopus ID: 2-s2.0-85073533401OAI: oai:DiVA.org:umu-164293DiVA, id: diva2:1362669
Funder
Marianne and Marcus Wallenberg Foundation, MMW 2017.0075The Jan Wallander and Tom Hedelius Foundation, P2015:0196:1Available from: 2019-10-21 Created: 2019-10-21 Last updated: 2024-07-02Bibliographically approved

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Angelov, Angel G.Ekström, MagnusKriström, Bengt

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CiteExportLink to record
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Citation style
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  • Other style
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Language
  • de-DE
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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