General Linear Models
General Linear Models (GLMs) form a unified underlying theory that covers simple and multiple linear regression techniques and general analysis of variance procedures for balanced and unbalanced data. An essential feature is the use of a normally-distributed residual or error term.
This course briefly presents the theory of General Linear Models and discusses their application and interpretation in problems of biological and medical sciences and in pharmaceutical work. Many examples are used to illustrate a wide range of GLMs.
Who Should Attend?
Statisticians who have experience with multiple regression and analysis of variance and have had some previous exposure to the analysis of variance for unbalanced data.
How You Will Benefit
Participants will gain confidence in correctly analysing different types of problems using GLMs. In particular, identifying the correct type of sums of squares to use will be of benefit in analysing real-life problems.
What Do We Cover?
Practical work will be done in: SAS
Note: For practical work participants must bring their own laptops with a full-licensed version of the software.