This course is for those who analyze the number of occurrences of an event or the rate of occurrence of an event as a function of some predictor variables. For example, the rate of insurance claims, colony counts for bacteria or viruses, the number of equipment failures, and the incidence of disease can be modeled using Poisson regression models.

This course includes practice data and exercises.

Learn how to

• fit Poisson regression models for discrete counts and rates
• assess the models for overdispersion
• fit negative binomial regression models
• fit zero-inflated Poisson models and zero-inflated negative binomial models
• perform model diagnostics with ODS graphics.

Who should attend

Biostatisticians, epidemiologists, social scientists, physical scientists, and business analysts

Formats available	Standard duration
e-Learning:	3.5 hours/180 day license	System Requirements

Before attending this course, you should be able to

• execute SAS programs and create SAS data sets
• fit and interpret linear regression and logistic regression models.

You can obtain this experience by completing the SAS Programming 1: Essentials and Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression courses.

This course addresses SAS/STAT software.

The Poisson Regression Model

• introduction to Poisson regression
• correction for overdispersion

Applications of Poisson Regression Models

• Poisson regression models for rates
• zero-inflated Poisson models and zero-inflated negative binomial models
• model diagnostics