Work

A Perspective on the Use of Poisson Versus Logistic Regression in Exposure–Response Analysis: Insights and Considerations

Year: 2025

Type: article

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.

Source: CPT Pharmacometrics & Systems Pharmacology

DOI: 10.1002/psp4.70100

Authors: Yiming Cheng, Ping Chen, Yan Li

Institution: Bristol-Myers Squibb (United States)

Language: English

Topic: Statistical Methods in Clinical Trials

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,140