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Course profile

Regression Modelling for Biostatistics 2 (STAT7619)

Study period
Sem 2 2024
Location
External
Attendance mode
Online

Course overview

Study period
Semester 2, 2024 (22/07/2024 - 18/11/2024)
Study level
Postgraduate Coursework
Location
External
Attendance mode
Online
Units
2
Administrative campus
Herston
Coordinating unit
Public Health School

This course presents the theory and application of generalised linear models (GLMs) and survival analysis, paying proper attention to the underlying assumptions of these models. The unit covers the implementation of GLMs 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 presents methods to analyse time to event survival data including the Kaplan Meier curve, the Cox proportional hazards model, and parametric accelerated failure time models. A major focus is on selection of appropriate methods, assessing the model fit and diagnostics of GLMs and survival models, and the practical interpretation and communication of model results.

The aim of this course is to enable students to implement generalized linear models (GLMs) for analysis of categorical data, and survival analysis methods for time-to-event data, with proper attention to the underlying assumptions. A major focus is on selection of appropriate methods, assessing the model fit and diagnostics of GLMs and survival models, and the practical interpretation and communication of model results.ᅠᅠ

Course requirements

Assumed background

This course builds on the material taught in STAT7618 Regression Modelling for Boistatistics 1 and covers generalized linear models and survival analysis techniques.

Prerequisites

You'll need to complete the following courses before enrolling in this one:

STAT7617, STAT7604

Incompatible

You can't enrol in this course if you've already completed the following:

STAT7608, STAT7609

Course contact

Course staff

Lecturer

Dr Michael Waller

Timetable

The timetable for this course is available on the UQ Public Timetable.