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The aim of the unit is to teach the use of Generalised Linear Models (GLMs) and Survival Analysis methods, with proper attention to the underlying assumptions of these models. The unit will teach how GLMs can be used to analyse count data using Poisson and Negative Binomial regression; how Logistic regression models can be applied to binary, multinomial, and ordinal data; and the use of GLMs with continuous data. The unit covers methods to analyse time to event survival data including the Kaplan Meier curve, the Cox proportional hazards model, and parametric accelerated failure time models. The unit will focus on methods to assess the model fit and diagnostics of GLMs and survival models, and the practical interpretation and communication of model results.
Study level | Postgraduate |
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Academic unit | Public Health |
Credit points | 6 |
Prerequisites:
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(BSTA5210 or BSTA5007) |
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Corequisites:
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None |
Prohibitions:
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BSTA5008 and BSTA5009 |
Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Session | MoA ? | Location | Outline ? |
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Semester 1 2024
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Online | Camperdown/Darlington, Sydney |
View
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Semester 2 2024
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Online | Camperdown/Darlington, Sydney |
View
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Session | MoA ? | Location | Outline ? |
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Semester 1 2025
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Online | Camperdown/Darlington, Sydney |
Outline unavailable
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Semester 2 2025
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Online | Camperdown/Darlington, Sydney |
Outline unavailable
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Find your current year census dates
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.