The Advanced Epidemiology Short Course is being held in Sydney, Australia at the University of Sydney.
What does the course include?
- An introduction to causal inference using contemporary approaches such as a potential approach model and directed acyclic graphs (DAGs).
- A comprehensive overview of systematic error (confounding, selection and information biases).
- An introduction to quantitative bias analysis methods to correct for systematic error in epidemiological studies. (Sometimes called sensitivity analyses.) Methods taught range from simple to probabilistic methods.
- Quantitative bias analysis exercises using Excel spreadsheets. Understanding and applying bias analyses not only enables you to undertake your own analyses in the future, but also means you have a deeper understanding of systematic error.
- Selected specific topics such as regression model building strategies, effect measure modification and interaction; direct and indirect effects (i.e. mediation analysis), propensity scores, instrument variables; null hypothesis significance testing and p values.
The course will be similar to previous years with the option to attend the four-day course, or just the final day on Thursday 28 September which focuses on applications of some of these methods in disease and cost effectiveness simulations (e.g. Markov and multistate lifetable models), and applications of recent methods using G Methods such as Marginal Structural Models (MSMs) and Causal Mediation Analysis. This course is taught by Prof Tony Blakely (University of Otago) and Prof John Lynch (University of Adelaide). Course details and registration can be found at: www.otago.ac.nz/wellington/advancedepicourse
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