The purpose of this course run by the Centre for Epidemiology and Biostatistics, in association with The University of Adelaide, is to provide a systematic overview of epidemiological concepts and methods, building up from sources of error (confounding, information bias, selection bias) to bias analysis methods, then a range of contemporary methods. The course is premised on a counterfactual and potential outcomes approach to epidemiology.
This course has been taught in Australia by Professor Tony Blakely and John Lynch for many years, and is highly regarded.
Date: 17-19 September, 2020
Venue: The University of Melbourne (exact location to be advised)
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.
Who is this course designed for?
The course is designed for 2 target audiences:
- PhD students, early career researchers, and advanced MPH students who wish to extend their knowledge to include some of the more advanced epidemiological ways of thinking and methods that have merged over the last decade.
- More senior investigators who want an efficient “catch up” on some of the new thinking and methods being used in higher quality research publications
This course will assume knowledge of study design and analytical methods, the basic principles of systematic error (confounding, selection and information biases) and biostatistics up to multivariable regression. For example, successful completion of a Diploma or Masters of Public Health course in epidemiology and biostatistics (or similar) will usually provide the necessary basis to undertake this course. If you wish to discuss your suitability for this course, please contact: email@example.com
CAUSATION, SYSTEMATIC ERRORS, QUANTITATIVE BIAS ANALYSIS
- Causal Concepts in Epidemiology
- Potential Outcomes Approach (POA) to Causation
- Directed Acyclic Graphs (DAGs)
- Workshop – Class exercise around constructing a DAG for death by shark attack
- Quantitative Bias Analysis (QBA)
- Understanding Selection Bias – an application of DAGs
- Selection Bias and QBA
- Understanding Confounding Bias
- Some Alternative Approaches to Control Confounding
- Confounding Bias QBA
- Information Bias
- Information Bias QBA
- Probabilistic Bias Analysis
- Multiple Bias Analysis
- Optional Sessions (depends on time and participant interests which ones we cover)
Tony Blakely’s research has included pioneering the development of methods to link census and health data (New Zealand Census-Mortality Study; Cancer Trends). He directs two HRC-funded research programmes: the Health Inequalities Research Programme (HIRP); the Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme (BODE³). Tony currently has appointments at both the University of Melbourne and the University of Otago. He has authored about 300 peer-reviewed publications, including many that include critique, development or application of epidemiological methods. Tony is well known for his enthusiastic and engaging style of presentation and teaching.
John Lynch is the Professor of Epidemiology and Public Health in the School of Public Health, at the University of Adelaide. He is also a Visiting Professor of Epidemiology in the School of Social and Community Medicine at the University of Bristol (UK). He has held academic positions at the University of Michigan (USA) and McGill University in Canada. John is an internationally recognised scholar in epidemiology and public health. He was one of the editors of the International Journal of Epidemiology from 2000 to 2016. His recent research involves early life interventions and he leads the NHMRC CRE, EMPOWER: Health systems, disadvantage and child well-being.
What do previous participants say about the course?
About 30 participants have completed the course each year since 2011, ranging from: recent students of a Diploma/Masters-level taught paper in epidemiology; to lecturers of the same; to senior epidemiologists. All participants would recommend the course to other colleagues, and at least three quarters rated the course 5 out of 5 on ‘content’ and ‘presentation’. Summary comments about the course included:
“This was by far the most useful short course I have ever done. It was an excellent summary of epidemiological advances. I would recommend it to anyone working in, or studying, epidemiology at a moderate to advanced level.” [Lecturer and convenor of Diploma/Masters-level epidemiology taught course.]
“I found the course highly useful in that it grounded what I had learnt in [Diploma/Masters course] and extended on this. Bits of the [Diploma/Masters course] were still a bit foggy; this course has definitely provided clarity. I also feel much better equipped to consider systematic error and how to address it.” [Recent student of Diploma/Masters-level epidemiology taught course.]
Applications for courses can be filled out online via eCart.
Applications close the day before the course date.
For participants registering close to the course date, please be informed that we may not be able to cater to extra requests or specific dietary requirements. We are also unable to guarantee the availability of complete participant materials for the course (name tags, completion certificates). Where completion certificates are not available these will be mailed out to you after the course.
Ph: +61 3 8344 6692
17th - 19th September, 2020
To Be Advised
The University of Melbourne
This course will assume knowledge of study design and analytical methods, the basic principles of systematic error (confounding, selection and information biases) and biostatistics up to multivariable regression.