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

Prerequisites

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(R) Programming I: Essentials and Statistics I: Introduction to ANOVA, Regression, and Logistic Regression courses.SAS Products Covered

SAS/STAT

Course Outline

The Poisson Regression Model

introduction to Poisson regression correction for overdispersionApplications of Poisson Regression ModelsPoisson regression models for rates zero-inflated Poisson models and zero-inflated negative binomial models model diagnostics