Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete (e.g. binary or frequency). This course covers: What are GLMs? When should we use ...

Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells ...

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

What is a Generalized Linear Model? A traditional linear model is of the form where y i is the response variable for the i th observation. The quantity x i is a column vector of covariates, or ...

Mixed Models Theory This section provides an overview of a likelihood-based approach to general linear mixed models. This approach simplifies and unifies many common statistical analyses, including ...

An introduction to the theory and application of generalised linear models for the analysis of continuous, categorical and count data, and regression models for survival data. Topics include: general ...

Multiple regression and regression diagnostics. Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals.