Research Supervisor Connect

Investigating causal mechanisms in motor control, paralysis and pain


This is an interesting and unique postgraduate opportunity to learn and apply modern statistical techniques to investigate causal effects under the causal framework.


Dr Joanna Diong.

Research location

Camperdown - Charles Perkins Centre

Program type



When investigators care about if or how treatments affect outcomes, they are fundamentally interested in causal mechanisms. Randomised controlled trials are the preferred study design to investigate causal effects of treatments on outcomes because randomisation ensures treated and control groups are balanced. However, randomised trials of sustained interventions are prone to post-randomisation confounding and selection bias, problems similar to those encountered in observational studies. Consequently, the analysis of data from randomised trials and observational studies require similar methods to identify and estimate treatment effects.

Overall, this series of studies will involve applying the causal inference framework to design studies and analysis plans that identify and estimate treatment effects in randomised trial and observational studies. These methods will be applied in separate projects over a range of clinical areas, including human neurophysiology, spinal cord injury, low back pain and physical activity.


Additional information

This project would suit a student with a background in epidemiology, public health, data science, or a related discipline. You will learn the causal inference framework and statistical approaches, and apply these methods to process and analyse data using modern computational techniques. We are passionate about good science, and aim to teach you responsible research practices in a stimulating environment.

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Opportunity ID

The opportunity ID for this research opportunity is 238

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