| Prescription: |
Brief outline of generalised linear model theory. Normal applications with linear models including nested designs, random effects and repeated measures. Count data, Poisson- based models, log-linear models, basic contingency tables. Overdispersion, quasi likelihoods,variance inflation factor. Binary responses, logit model and repeated measurements with binary data. Ordinal response models (proportional odds model, adjacent category logit model, etc). Generalised linear mixed models. Co-taught with STAT 438. |
