ArticleCPT: pharmacometrics & systems pharmacology2025
A Perspective on the Use of Poisson Versus Logistic Regression in Exposure-Response Analysis: Insights and Considerations.
Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This perspective evaluates the use of Poisson versus logistic regression in modeling binary exposure-response (ER) data. Through simulation studies across varying sample sizes, event rates, and ER slopes, we highlight the strengths and limitations of each method. Our findings show that Poisson regression is suitable under low event rates, while logistic regression provides consistent performance across broader scenarios. These insights help guide model selection and improve the robustness of ER analyses in drug development.
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