Date Subject Code
1-10 Experiments, observational studies, and models
1-15 Introduction to R [R] [Rnw]
1-17 Transformations [R] [SAS]
1-24 Generalized linear models
1-29 Maximum likelihood estimation [R]
1-31 Exponential families
2-5 Sampling distribution of GLM regression coefficients [R]
2-7 Weighted least squares [R] [SAS]
2-19 GLM estimation and model fitting
2-21 Logistic regression [R] [SAS]
2-28 Logistic regression: Probabilities and odds ratios [R] [SAS]
3-19 Inference: Likelihood ratio vs. Wald approaches [R] [SAS]
3-26 Diagnostics and residuals [R] [SAS]
3-28 Model comparison [R] [SAS]
4-2 Model building: Case study [R] [SAS]
4-9 Poisson regression [R] [SAS]
4-11 Offsets and overdispersion [R] [SAS]
4-18 Multinomial regression [R] [SAS]
4-23 Proportional odds models [R] [SAS]