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Subject details

  • Topics
    • 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
  • Study resources
    • Instructional Methods
      • Disscusion forum/Discussion Board
      • Online Quizzes/Tests
      • Online assignment submission
      • Podcasting/Leacture capture
      • Standard Media
      • Web links
    • Print Materials
      • Welcome letter
    • Online Materials
      • Printable format materials

Student who successfully complete this subject will be able to:

  1. Appraise how the type of data and the nature of the research questions affects the appropriate analysis methodology
  2. Contrast a range of advanced regression techniques, testing assumptions appropriately
  3. Assess logistic regression analyses for binary, ordinal and nominal response variables
  4. Contrast GEEs, Mixed and Multi-level Modelling analyses for nested and repeated measures data for nominal and metric response variables
  5. Formulate and report on appropriate Survival Analysis models using Cox Regression and Time Dependent Covariates
  6. Identify the most appropriate method of regression analysis in any particular research context.
  • Assignment 1 - Assignments — 2 (40%)
  • Assignment 2 - Quizzes — Online (10%)
  • Assignment 3 - Invigilated Exam (50%)

Textbooks are subject to change within the academic year. Students are advised to purchase their books no earlier than one to two months before the start of a subject

Entry Requirements

Equivalent Subjects

You cannot enrol in this unit if you have successfully completed any of the following subject(s) because they are considered academically equivalent:

  • SWI-HMS793

You must have successfully completed the following subject(s) before starting this subject:

Special requirements

No special requirements

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.

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