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Gain-probability diagrams as an alternative to significance testing in economics and finance

Author

Listed:
  • David Trafimow
  • Ziyuan Wang
  • Tingting Tong
  • Tonghui Wang

Abstract

Purpose - The purpose of this article is to show the gains that can be made if researchers were to use gain-probability (G-P) diagrams. Design/methodology/approach - The authors present relevant mathematical equations, invented examples and real data examples. Findings - G-P diagrams provide a more nuanced understanding of the data than typical summary statistics, effect sizes or significance tests. Practical implications - Gain-probability diagrams provided a much better basis for making decisions than typical summary statistics, effect sizes or significance tests. Originality/value - G-P diagrams provide a completely new way to traverse the distance from data to decision-making implications.

Suggested Citation

  • David Trafimow & Ziyuan Wang & Tingting Tong & Tonghui Wang, 2023. "Gain-probability diagrams as an alternative to significance testing in economics and finance," Asian Journal of Economics and Banking, Emerald Group Publishing Limited, vol. 7(3), pages 333-357, July.
    • Handle: RePEc:eme:ajebpp:ajeb-05-2023-0045
    DOI: 10.1108/AJEB-05-2023-0045
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