Advanced Topics in Regression B: (STAA0010B)Back to Intranet events
|Date:||Five 3 hourly sessions Tuesdays 11/4-9/5|
|Time:||5:30PM to 8:30PM|
|Venue:||BA513 Hawthorn Campus|
Dates: Five 3 hourly sessions Tuesdays 11/4-9/5 (5.30 – 8.30 pm)
Assumed Knowledge: Multiple Linear Regression (eg STAA0005A)
Software used: IBM SPSS Statistics Version 24
Maximum 20 students
Statistical techniques as listed below will be covered with an emphasis on the interpretation and reporting of these results.
When observations are clustered or auto-correlated conventional methods cannot be used. Such data is very common in practise and one of the advantages of these models is the way in which missing values can be handled. Generalised Estimating Equations and Mixed Linear Models are initially introduced to solve this problem. For more sophisticated problems HLM7 is a free student software package can be used. This software allows the fitting of longitudinal models and can handle response variables with a variety of distributions. Models are fitted separately for each subject and then combined to produce a population averaged model.
Survival analysis follows. Kaplan Meier, Cox regression and Covariate dependent Models.
Online quizzes will be available for self-assessment.