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Poisson Regression

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May 1, 2024 4 minute read

Poisson regression is a statistical technique used to model the number of events that occur within a fixed interval of time or space. It is a type of generalized linear model (GLM) that assumes that the outcome variable is a count variable, and that the logarithm of the mean of the outcome variable is a linear function of the predictor variables. Poisson regression is commonly used in fields such as epidemiology, healthcare, insurance, and finance to model the occurrence of events such as the number of hospital admissions, the number of insurance claims, or the number of financial transactions over a given period of time.

What is Poisson Regression Used For?

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Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Poisson Regression.
Seminal work on generalized linear models, providing the theoretical foundation for Poisson regression.
Comprehensive overview of Poisson regression and related models, suitable for advanced undergraduates and graduate students.
Detailed treatment of Poisson regression in the context of epidemiology, including case studies and applications.
Practical guide to statistical methods in medical research, including Poisson regression.
Accessible and practical guide to Poisson regression for social scientists, with a focus on understanding the results.
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