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Statistical significance in choice modelling: computation, usage and reporting

Author

Listed:
  • Stephane Hess
  • Andrew Daly
  • Michiel Bliemer
  • Angelo Guevara
  • Ricardo Daziano
  • Thijs Dekker

Abstract

This paper offers a commentary on the use of notions of statistical significance in choice modelling. We argue that, as in many other areas of science, there is an over-reliance on 95% confidence levels, and misunderstandings of the meaning of significance. We also observe a lack of precision in the reporting of measures of uncertainty in many studies, especially when using p-values and even more so with star measures. The paper provides a precise discussion on the computation of measures of uncertainty and confidence intervals, discusses the use of statistical tests, and also stresses the importance of considering behavioural or policy significance in addition to statistical significance.

Suggested Citation

  • Stephane Hess & Andrew Daly & Michiel Bliemer & Angelo Guevara & Ricardo Daziano & Thijs Dekker, 2025. "Statistical significance in choice modelling: computation, usage and reporting," Papers 2506.05996, arXiv.org, revised Jun 2025.
    • Handle: RePEc:arx:papers:2506.05996
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