The Probability of Improved Prediction: a new concept in statistical inference
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916262015139840 |
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| author | Thas, Olivier Jaspers, Stijn |
| author_facet | Thas, Olivier Jaspers, Stijn |
| contents | In an attempt to provide an answer to the increasing criticism against p-values and to bridge the gap between statistical inference and prediction modelling, we introduce the probability of improved prediction (PIP). In general, the PIP is a probabilistic measure for comparing two competing models. Three versions of the PIP and several estimators are introduced and the relationships between them, p-values and the mean squared error are investigated. The performance of the estimators is assessed in a simulation study. An application shows how the PIP can support p-values to strengthen the conclusions or possibly point at issues with e.g. replicability. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2405_17064 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Probability of Improved Prediction: a new concept in statistical inference Thas, Olivier Jaspers, Stijn Methodology In an attempt to provide an answer to the increasing criticism against p-values and to bridge the gap between statistical inference and prediction modelling, we introduce the probability of improved prediction (PIP). In general, the PIP is a probabilistic measure for comparing two competing models. Three versions of the PIP and several estimators are introduced and the relationships between them, p-values and the mean squared error are investigated. The performance of the estimators is assessed in a simulation study. An application shows how the PIP can support p-values to strengthen the conclusions or possibly point at issues with e.g. replicability. |
| title | The Probability of Improved Prediction: a new concept in statistical inference |
| topic | Methodology |
| url | https://arxiv.org/abs/2405.17064 |