A more interpretable regression model for count data with excess of zeros
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909814777446400 |
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| author | Pereira, Gustavo H. A. Leão, Jeremias Santos-Neto, Manoel Cai, Jianwen |
| author_facet | Pereira, Gustavo H. A. Leão, Jeremias Santos-Neto, Manoel Cai, Jianwen |
| contents | Count data are common in medical research. When these data have more zeros than expected by the most used count distributions, it is common to employ a zero-inflated regression model. However, the interpretability of these models is much lower than the most used count regression models. In this work, we introduce a more interpretable regression model for count data with excess of zeros based on a reparameterization of the zero-inflated Poisson distribution. We discuss inferential and diagnostic tools and perform a Monte Carlo simulation study to evaluate the performance of the maximum likelihood estimator. Finally, the usefulness of the proposed regression model is illustrated through an application on children mortality. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_24916 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A more interpretable regression model for count data with excess of zeros Pereira, Gustavo H. A. Leão, Jeremias Santos-Neto, Manoel Cai, Jianwen Methodology Count data are common in medical research. When these data have more zeros than expected by the most used count distributions, it is common to employ a zero-inflated regression model. However, the interpretability of these models is much lower than the most used count regression models. In this work, we introduce a more interpretable regression model for count data with excess of zeros based on a reparameterization of the zero-inflated Poisson distribution. We discuss inferential and diagnostic tools and perform a Monte Carlo simulation study to evaluate the performance of the maximum likelihood estimator. Finally, the usefulness of the proposed regression model is illustrated through an application on children mortality. |
| title | A more interpretable regression model for count data with excess of zeros |
| topic | Methodology |
| url | https://arxiv.org/abs/2509.24916 |