Te mātauranga urutā whatutoto
Tuesday - Friday, 20-23 February 2018
NEW for 2018... The length of this course has been extended from 3 to 4 days and includes more case studies (led by Associate Professor Rebecca Bentley, University of Melbourne) and a half-day of epidemiological and economic modelling of health sector interventions. Registrations are welcome either for the first three days or for all four days. Or if you have attended this course in previous years, you may wish to register for Day 4 only.
Advanced epidemiology is a 4-day course which covers intermediate to advanced-level epidemiological methods. The main focus of the course is gaining an in-depth, and ‘modern’, understanding of the three sources of systematic error in epidemiological studies: selection, confounding and information biases.
Quantitative bias analysis methods will also be demonstrated and run as class exercises, the premise being that it assists a deeper understanding of systematic error as well as equipping course attendees with methods to correct for these biases. Additional selected topics are also covered, including a reframing of confounding to include contemporary counterfactual and an overview ‘G methods’.
This year a fourth day is added allowing more time for class discussion, and introducing more topics (e.g. natural experiments, epidemiological and economic simulation modelling, causal mediation analyses).
The course is suited to students who have completed an introductory level course in epidemiology (e.g. Diploma or Masters of Public Health paper in epidemiology and biostatistics), through to practicing epidemiologists wanting an update.
- A comprehensive overview of systematic error (confounding, selection and information biases), using contemporary approaches such as a counterfactual model, directed acyclic graphs (DAGs) and g-methods.
- An introduction to quantitative bias analysis methods to correct for systematic error in epidemiological studies. (Sometimes called sensitivity analyses.) Methods taught will range from simple single bias adjustment, to adjusting for multiple biases using probabilistic methods.
- Selected intermediate to advanced epidemiological topics:
- Directed acyclic graphs (DAGs)
- Imputation for missing data
- Effect measure modification and interactions
- G-methods (e.g. marginal structural models, g-formula and g-computation)
- Estimating direct and indirect effects (i.e. causal mediation analysis)
- Alternative methods for addressing confounding: propensity scores, instrument variables, difference in difference, fixed effects.
- Epidemiology meets health economics; simulating the impact of health interventions on future health gains and costs.
Style of course
Small group - i.e. teaching and discussion in a group of up to 25 people
Who should attend?
This course will assume a basic knowledge of epidemiology study design and analytical methods, systematic error (confounding, selection and information biases) and biostatistics. For example, successful completion of a Diploma or Masters of Public Health paper in epidemiology and biostatistics (or similar) will provide the necessary basis to undertake this course.
About 20 participants completed the inaugural 2011 course, 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].
Draft timetable, course materials and resources
- Professor Tony Blakely - University of Otago and University of Melbourne. Tony's research has included pioneering the development of methods to link census and health data (New Zealand Census-Mortality Study; CancerTrends). He directs two HRC-funded research programmes: the Health Inequalities Research Programme (HIRP); the Burden of Disease Epidemiology, Equity and Cost-Effectiveness programme (BODE3). He has authored about 150 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.
- Associate Professor Rebecca Bentley, University of Melbourne. Rebecca is a Principal Research Fellow in Social Epidemiology in the Centre for Health Equity, Melbourne School of Population and Global Health. Over the past ten years, Rebecca has developed a research program exploring the role of housing and residential location in shaping health and wellbeing in Australia, using advanced quantitative methods. This research has a particular focus on housing affordability, tenure and their measureable effects on individual health and wellbeing. Rebecca is currently an ARC Future Fellow undertaking research focussed on housing affordability and socio-economic and wellbeing outcomes in Australia.
Course cost and registration
Each day of this course costs $300 early bird, or $400 after 20 December 2017.
A 50% discount is available to full-time students, those unwaged and University of Otago staff.
How to register
To register for the full 4-days, please choose the box for Advanced Epidemiology Day 1-3 day AND the box for Advanced Epidemiology Day 4.
To register for the first 3 days only, please choose the box for Advanced Epidemiology Day 1- 3 day.
To register for the final day only, please choose the box for Advanced Epidemiology Day 4.