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Distribution-free tests of stochastic dominance for small samples
Citation
Heathcote, A and Brown, S and Wagenmakers, EJ and Eidels, A, Distribution-free tests of stochastic dominance for small samples, Journal of Mathematical Psychology, 54 pp. 454 -463. ISSN 0022-2496 (2010) [Refereed Article]
Copyright Statement
Copyright 2010 Elsevier Inc.
DOI: doi:10.1016/j.jmp.2010.06.005
Abstract
One variable is said to ``stochastically dominate'' another if the probability of observations smaller than x is greater for one variable than the other, for all x. Inferring stochastic dominance from data samples is important for many applications of econometrics and experimental psychology, but little is known about the performance of existing inferential methods. Through simulation, we show that three of the most widely used inferential methods are inadequate for use in small samples of the size commonly
encountered in many applications (up to 400 observations from each distribution). We develop two new inferential methods that perform very well in a limited, but practically important, case where the two variables are guaranteed not to be equal in distribution. We also show that extensions of these new methods, and an improved version of an existing method, perform quite well in the original, unlimited case.
Item Details
Item Type: | Refereed Article |
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Keywords: | Stochastic dominance, Semiparametric and non-parametric methods, Bootstrap methods, Bayesian analysis |
Research Division: | Psychology |
Research Group: | Cognitive and computational psychology |
Research Field: | Decision making |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in psychology |
UTAS Author: | Heathcote, A (Professor Andrew Heathcote) |
ID Code: | 98894 |
Year Published: | 2010 |
Web of Science® Times Cited: | 27 |
Deposited By: | Medicine |
Deposited On: | 2015-03-06 |
Last Modified: | 2015-05-11 |
Downloads: | 0 |
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