Overview
Sophisticated modelling techniques are essential for the analysis of real-world health data. Building on Health Data Analytics: Statistical Modelling I (HDAT9600), this course expands the statistical toolkit and broadens your understanding of relevant statistical approaches for the analysis of realistically complex data structures and research questions. The course is aimed … For more content click the Read More button below.
Topics covered in this course include multilevel models for hierarchical data; analysis of time series and longitudinal data; causal directed acyclic graphs (DAGs) and quasi-experimental approaches to inform causal analysis of observational data; and multiple imputation for missing values.
Content is delivered through a combination of online readings, expert guest lectures and practical hands-on tutorials. Statistical concepts are illustrated with a variety of health examples, and you will learn how to implement methods using leading statistical software.
Conditions for Enrolment
Prerequisites: HDAT9200 AND HDAT9600
Delivery
Multimodal - Standard (usually weekly or fortnightly)
Fully online - Standard (usually weekly or fortnightly)
Fees
Type | Amount |
---|---|
Commonwealth Supported Students (if applicable) | $1165 |
Domestic Students | $4650 |
International Students | $6060 |
Pre-2019 Handbook Editions
Access past handbook editions (2018 and prior)