 1. Basic Concepts
 1.1 Introduction
 1.2 Outline of generalized linear model
 1.3 Model estimation: background
 1.4 Model estimation: IRLS
 1.5 Measuring the goodness of fit
 1.6 Residuals
 Appendix: exponential family
 2. Binary Data
 2.1 Introduction
 2.2 Binomial distribution
 2.3 Modelling
 2.4 Measuring the goodness of fit
 2.5 Other topics
 3. Polytomous Data
 3.1 Introduction
 3.2 Measurement scales and modelling
 3.3 The multinomial distribution
 3.4 Likelihood function
 3.5 Deviance function and overdispersion
 4. Loglinear Models
 4.1 Introduction
 4.2 Likelihood functions
 4.3 Overdispersion
 4.4 Comparison of Poisson means
 4.5 Multinomial response models
 4.6 Multiple responses (I): joint dependence of response variable
 4.6 Multiple responses (II): multivariate regression models
 4.6 Multiple responses (III): likelihood equations
 5. Conditional Likelihood
 5.1 Introduction
 5.2 Marginal likelihood
 5.3 Conditional likelihood
 5.4 Conditional likelihood for exponential family
 5.5 Profile likelihood
 5.6 Hypergeometric distribution
 5.7 Noncentral hypergeometric distribution
 5.8 Some applications involving binary data
 5.9 Some applications involving polytomous data
 6. QuasiLikelihood Functions
 6.1 Introduction
 6.2 Independent observations
 6.3 Dependent observations
 7. Models for Survival Data
 7.1 Introduction
 7.2 Estimation of survival function
 7.3 Comparison of two groups of survival data
 7.4 Proportional hazards model
 8. Model Checking
 8. Model checking
 Exams
 Midterm (2002)
 Midterm (2004)
 Final (2002)
 Final (2004)
 Homework and Download
 Homework 1
 Homework 1 (solution)
 Homework 2
 Download Files
