Course overview
This course focuses on conceptual and practical issues in the design, interpretation and appraisal of epidemiological research. There is a particular emphasis on improving causal inference through design and analysis. The course content builds on the introductory courses in both epidemiology and biostatistics. Practical and tutorial sessions will provide hands-on experience with the concepts and techniques discussed in lectures.
Course learning outcomes
- Understand the different roles of descriptive, predictive and causal epidemiology
- Appreciate the importance and basic principles of high quality descriptive epidemiology
- Understand the role and basic principles of high quality predictive epidemiology
- Understand different types of causal thinking that have been historically used, and are currently used in epidemiology
- Capture a theoretical causal model using Directed Acyclic Graphs (DAG)
- Understand the potential outcomes approach (POA) to causation
- Understand and identify potential sources of systematic error (bias) arising from confounding, selection and information biases
- Understand potential methods to reduce confounding, selection and information bias
- Understand and apply correct interpretations of P values and confidence intervals as measures of “uncertainty”
- Understand the different methods to support causal inference – RCTs, quasi-experiments, and observational
Availability
Class details
Adelaide City Campus East
Group 1
Class number 57176
Section WS01
Size 30
Available 12
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