Advanced Statistical Modelling
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- 25 Feb 2019
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Students who successfully complete this subject 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 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
- Discussion forum/Discussion Board
- Online Quizzes/Tests
- Online assignment submission
- Podcasting/Lecture capture
- Standard Media
- Web links
- Welcome letter
- Printable format materials
You cannot enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
You must have successfully completed the following subject(s) before starting this subject:
- OtherDetails -
Students require access to a recent version of SPSS-Grad Pak at the least.
Students will learn 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
- Quizzes - Online (10%)
- Assignments - 2 (40%)
- Invigilated Examination (50%)
Textbook information is pending.