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A new method for constructing exact tests without making any assumptions

  • Karl Schlag

We present a new method for constructing exact distribution-free tests (and confidence intervals) for variables that can generate more than two possible outcomes. This method separates the search for an exact test from the goal to create a non- randomized test. Randomization is used to extend any exact test relating to means of variables with finitely many outcomes to variables with outcomes belonging to a given bounded set. Tests in terms of variance and covariance are reduced to tests relating to means. Randomness is then eliminated in a separate step. This method is used to create confidence intervals for the difference between two means (or variances) and tests of stochastic inequality and correlation.

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Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1109.

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Date of creation: Aug 2008
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Handle: RePEc:upf:upfgen:1109
Contact details of provider: Web page: http://www.econ.upf.edu/

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  1. Reiczigel, Jeno & Zakarias, Ildiko & Rozsa, Lajos, 2005. "A Bootstrap Test of Stochastic Equality of Two Populations," The American Statistician, American Statistical Association, vol. 59, pages 156-161, May.
  2. Joseph P. Romano & Michael Wolf, 2001. "Explicit Nonparametric Confidence Intervals For The Variance With Guaranteed Coverage," Statistics and Econometrics Working Papers ws010302, Universidad Carlos III, Departamento de Estadística y Econometría.
  3. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer, vol. 12(2), pages 153-157, June.
  4. Djankov, Simeon & La Porta, Rafael & Lopez-de-Silanes, Florencio & Shleifer, Andrei, 2008. "The law and economics of self-dealing," Journal of Financial Economics, Elsevier, vol. 88(3), pages 430-465, June.
  5. Africa Borges del Rosal & Concepción San Luis & Alfonso Sánchez-Bruno, 2003. "Dominance Statistics: A Simulation Study on the d Statistic," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 303-316, August.
  6. Karl Schlag, 2008. "Bringing game theory to hypothesis testing: Establishing finite sample bounds on inference," Economics Working Papers 1099, Department of Economics and Business, Universitat Pompeu Fabra.
  7. Fishman, George S., 1991. "Confidence intervals for the mean in the bounded case," Statistics & Probability Letters, Elsevier, vol. 12(3), pages 223-227, September.
  8. Nancy Buchan & Rachel Croson, 1999. "Gender and Culture: International Experimental Evidence from Trust Games," American Economic Review, American Economic Association, vol. 89(2), pages 386-391, May.
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