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Categorical Data: Models and Methods (MAST90099)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: MSPGH Website
- Email: Enquiry Form
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
Introduction to and revision of conventional methods for contingency tables especially in epidemiology:
- Odds ratios and relative risks;
- Chi-squared tests for independence;
- Mantel Haenszel methods for stratified tables;
- Methods for paired data.
The exponential family of distributions;
- Generalized Linear Models (GLMs);
- Parameter estimation for GLMs;
- Inference for GLMs, including the use of score, Wald and deviance statistics (including residuals) for confidence intervals and hypothesis tests.
Binary variables and logistic regression models:
- Methods for assessing model adequacy;
- Nominal and ordinal logistic regression for categorical response variables with more than two categories;
Count data and Poisson regression models:
- Log-linear models.
Software:
- Fitting GLMs in Stata and R.
Intended learning outcomes
- Understand the mathematical theory behind generalised linear models (GLMs) to analyse categorical data with proper attention to the underlying assumptions.
- Appreciate that most conventional methods of analysis of contingency table data are special cases of GLMs.
- Operate the Stata and R statistical packages to fit GLMs to data, extract, summarise, present and report the results.
- Emphasise the importance of the practical interpretation and communication of results to colleagues and clients who are not statisticians.
Generic skills
- Independent problem solving,
- Facility with abstract reasoning,
- Clarity of written expression,
- Sound communication of technical concepts
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
- POPH90014 Epidemiology 1 OR POPH90016 Epidemiology
- POPH90148 Probability and Distribution Theory
- MAST90100 Inference Methods in Biostatistics OR POPH90017 Principles of Statistical Inference
- MAST90102 Linear Regression OR POPH90120 Linear Models (either may be taken concurrently)
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
- Practical exercise 1 (approx 4 hours of work, approx 600 words, no more than 4 pages) due in Week 2 (10%)
- Practical exercise 2 (approx 4 hours of work, approx 600 words, no more than 4 pages) due in Week 4 (10%)
- Major assignment 1 (approx 10 hours of work, approx 1900 words, no more than 10 pages) due in Week 8 (30%)
- Practical exercise 3 (approx 4 hours of work, approx 600 words, no more than 4 pages) due in Week 10 (10%)
- Major assignment 2 (approx 12 hours of work, approx 2300 words, no more than 12 pages) due in Week 12 (40%)
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Lyle Gurrin Mode of delivery On Campus (Parkville) Contact hours 30 hours Total time commitment 170 hours Teaching period 29 July 2019 to 27 October 2019 Last self-enrol date 9 August 2019 Census date 31 August 2019 Last date to withdraw without fail 27 September 2019 Assessment period ends 22 November 2019 Semester 2 contact information
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: MSPGH Website
- Email: Enquiry Form
Time commitment details
170 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Resources Provided to Students online: Course notes and assignments.
Special Computer Requirements: Stata and R (open access) statistical software. - Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Biostatistics Course Master of Biostatistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022