Outline – For Now

Unit 5: Multiple Logistic Regression

  • Multiple Logistic Regression
  • Interactions
  • Confounding and Multicollinearity
  • Predictions
  • Model Validation and Potential Solutions to Violations

Unit 6: Model Selection

  • General Concepts
  • Linear Regression: Criteria based upon R-squared, Adjusted R-squared, and AIC
  • Automatic Selection Procedures
    • Forward Selection
    • Backward Elimination
    • (Forward) Stepwise Selection
  • Purposeful Selection

Unit 7: Poisson Regression and Generalized Linear Models

  • Poisson Distribution
  • Poisson Regression
  • Connection of Linear, Logistic, and Poisson Regrssion to GLMs