Standard syllabus
Generalized linear models · Graduate · Statistics
Topics
GLM framework
- Exponential family distributions
- Link functions and linear predictors
- Iteratively reweighted least squares
- Deviance and analysis of deviance
- Quasi-likelihood for overdispersion
Common models
- Logistic regression for binomial data
- Poisson and negative binomial regression
- Gamma regression for continuous positive data
- Ordinal and multinomial models (introduction)
- Zero-inflated and hurdle models (overview)
Diagnostics and extensions
- Residuals for GLMs: Pearson and deviance
- Influence and separation in logistic regression
- Generalized additive models (introduction)
- GEE for correlated data (preview)
Pricing
Graduate-level rates are set on consultation. See the pricing page for K–12 and undergraduate rates.