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

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)