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Advanced Topics in Regression
Postgraduate | SWI-STA80004 | 2019
Course information for 2019 intake
Expand your statistics skillset with advanced modeling techniques. Revive your survival analysis methods to measure and model events over time. You’ll learn several methods of regression analysis, and be able to apply them in a research setting.
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Entry requirements
- Part of a degree
- Duration
- -
FEE-HELP available
Advanced Topics in Regression
About this subject
Student who successfully complete this subject will be able to:
- Appraise how the type of data and the nature of the research questions affects the appropriate analysis methodology
- Contrast a range of advanced regression techniques, testing assumptions 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.
- 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
To introduce more advanced modelling techniques, including ordinal and multinomial logistic regression, generalised linear models, GEEs, mixed models, multi-level models and survival analysis.
Please note: assessment values are indicative only, details will be advised at the start of the subject.
- Assignments — 2 (40%)
- Quizzes — Online (10%)
- Invigilated Exam (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Prior study
You must have successfully completed the following subject(s) before starting this subject:
one of
- SWI-STA70002-Multivariate Statistics
SWI-HMS780 (Not currently available)
Equivalent subjects
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
SWI-HMS793 (Not currently available)
Additional requirements
- Other requirements -
Students require access to a recent version of SPSS - Grad Pak at the least.
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.