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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2506.05996 |
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| _version_ | 1866913131238785024 |
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| author | Hess, Stephane Daly, Andrew Bliemer, Michiel Guevara, Angelo Daziano, Ricardo Dekker, Thijs |
| author_facet | Hess, Stephane Daly, Andrew Bliemer, Michiel Guevara, Angelo Daziano, Ricardo Dekker, Thijs |
| contents | This paper offers a commentary on the use of notions of statistical significance in choice modelling. We review the reasons for uncertainty in parameter estimates, provide a precise discussion on the computation of measures of uncertainty and confidence intervals, and discuss the use of statistical tests. 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 \emph{star} measures. The paper also stresses the importance of considering behavioural or policy significance in addition to statistical significance. Finally, we stress a number of points that are specific to choice modelling and which require special attention, notably in relation to derived measures such as willingness-to-pay, the treatment of random heterogeneity, and the use of repeated choice data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05996 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Statistical significance in choice modelling: computation, usage and reporting Hess, Stephane Daly, Andrew Bliemer, Michiel Guevara, Angelo Daziano, Ricardo Dekker, Thijs Econometrics This paper offers a commentary on the use of notions of statistical significance in choice modelling. We review the reasons for uncertainty in parameter estimates, provide a precise discussion on the computation of measures of uncertainty and confidence intervals, and discuss the use of statistical tests. 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 \emph{star} measures. The paper also stresses the importance of considering behavioural or policy significance in addition to statistical significance. Finally, we stress a number of points that are specific to choice modelling and which require special attention, notably in relation to derived measures such as willingness-to-pay, the treatment of random heterogeneity, and the use of repeated choice data. |
| title | Statistical significance in choice modelling: computation, usage and reporting |
| topic | Econometrics |
| url | https://arxiv.org/abs/2506.05996 |