This is an overview of learning material in the course TMA4315 Generalized linear models given at the Department of Mathematical Sciences at NTNU. Course description with formal information.

Module pages

These are links to (html-versions of) module pages in TMA4315 Generalized linear models, that was held in the autumn semester in 2017 at NTNU. (To see .Rmd and .pdf just use in place of .html).

  1. Introduction
  2. Multiple linear regression
  3. Binary regression
  4. Poisson and gamma regression
  5. GLM in general and quasi likelihood
  6. Linear mixed models
  7. Generalized linear mixed models
  8. Summing up

Compulsory exercises

Suggested changes for 2018

  • Applied for digital exam.

Reading list

  • M1 (w1): one week - add stuff on working in groups, and theoretical exercises and group kahoot?
  • M2 (w2-3) : One week with model and estimation and one with inference. More theory on likelihoods already in Module 2, sequential anova and dummy coding, interactions (the stuff not covered so well in TMA4267/68). Also first pass with Wald, score, LRT and deviance.
  • M3: More on other links than logit in Module 3, test for overdispersion, maybe also mention lasso and ridge penalty. Only two weeks.
  • M4: More on offset models for Poisson.
  • More theory on likelihoods and orthogonality++ in Module 5.
  • Add module on multinomial models and contingency tables - new M6