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Unit of study_

BSTA5017: Causal Inference (CSI)

2024 unit information

This unit covers modern statistical methods that are now available for assessing the causal effect of a treatment or exposure from a randomised or observational study. The unit begins by explaining the fundamental concept of counterfactuals or potential outcomes and introduces causal diagrams (or directed acyclic graphs) to visually identify confounding, selection and other biases that prevent unbiased estimation of causal effects. Key issues in defining causal effects that are able to be estimated in a range of contexts are presented using the concept of the target trial to clarify exactly what the analysis seeks to estimate. A range of statistical methods for analysing data to produce estimates of causal effects are then introduced. Propensity score and related methods for estimating the causal effect of a single time point exposure are presented, together with extensions to longitudinal data with multiple exposure measurements, and methods to assess whether the effect of an exposure on an outcome is mediated by one or more intermediate variables. Comparisons will be made with conventional statistical methods. Emphasis will be placed on interpretation of results and understanding the assumptions required to allow inferences to be called causal. Stata and R software will be used to apply the methods to real datasets.

Unit details and rules

Managing faculty or University school:

Public Health

Code BSTA5017
Academic unit Public Health
Credit points 6
BSTA5210 or BSTA5211 or (BSTA5007 and BSTA5008)
Assumed knowledge:

At the completion of this unit, you should be able to:

  • LO1. Use counterfactuals (potential outcomes) to precisely define causal effects
  • LO2. Describe the differences between association and causation, and the fundamental assumptions required for causation
  • LO3. Construct causal diagrams and use them to identify potential sources of bias
  • LO4. Implement causal inference methods, using software, for single time point and longitudinal exposures, and for mediation analyses
  • LO5. Interpret results of analyses in light of the causal assumptions required
  • LO6. Effectively communicate results of causal analyses in language suitable for a clinical or epidemiological journal

Unit availability

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 ? 
Semester 1 2024
Online Camperdown/Darlington, Sydney
Session MoA ?  Location Outline ? 
Semester 2 Early 2020
Online Camperdown/Darlington, Sydney
Outline unavailable
Semester 2 2021
Online Camperdown/Darlington, Sydney
Semester 2 2022
Online Camperdown/Darlington, Sydney
Semester 2 2023
Online Camperdown/Darlington, Sydney

Modes of attendance (MoA)

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.