Overview

To introduce more advanced modelling techniques, including ordinal and multinomial logistic regression, generalised linear models, GEEs, mixed models, multi-level models and survival analysis.

Requisites

Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date

Learning outcomes

Students who successfully complete this unit will be able to:

  • Appraise how the type of data and the nature of the research questions affect the appropriate analysis methodology
  • Contrast a range of advanced regression techniques, testing assumptions and managing missing data appropriately
  • Assess logistic regression analyses for binary, ordinal and nominal response variables
  • Contrast GEEs, Mixed and Multi-level Modelling analyses for nested and repeated measures data for nominal and metric response variables
  • Formulate and report on appropriate Survival Analysis models using Cox Regression and Time Dependent Covariates
  • Identify the most appropriate method of regression analysis in any particular research context

Teaching methods

Hawthorn Online

Type Hours per week Number of weeks Total (number of hours)
Online Contact (Phasing out)
Collaboration
1.00 4 weeks 4
Online
Directed Online Learning and Independent Learning
11.33 12 weeks 136
TOTAL140

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Face to Face Contact (Phasing out)
Lecture
3.00 12 weeks 36
Specified Learning Activities (Phasing out)
Readings
2.00 12 weeks 24
Unspecified Learning Activities (Phasing out)
Independent Learning
7.50 12 weeks 90
TOTAL150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 40% 3,4,5 
ExaminationIndividual 50% 2,5,6 
Online QuizIndividual 10% 1,2 

Content

  • Multiple regression
  • General linear model
  • Generalised linear model
  • Logistic regression for binary, nominal and ordinal data
  • Generalised Estimating Equations and Mixed models
  • Multi-level modelling
  • Survival analysis
  • Managing missing data

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.