Learning objectives

  1. Define log-linear models in GLM framework
  2. Identify situations that motivate use of log-linear models
  3. Define the Poisson distribution and the log-linear Poisson GLM
  4. Identify applications and properties of the Poisson distribution
  5. Define multi-collinearity


  1. Brief review of GLMs
  2. Motivating example for log-linear models
  3. Poisson log-linear GLM
  4. Note on multicollinearity

Reading: Vittinghoff textbook chapter 8.1-8.3


Learning Objectives

  1. Simulate Poisson-distributed data with a relevant covariate
  2. Fit a Poisson log-linear GLM
  3. Create and interpret diagnostic plots for a log-linear GLM
  4. Use analysis of deviance to compare two log-linear GLMs
  5. Practice recoding and creating tables and plots