AUSTRALASIAN EPIDEMIOLOGICAL ASSOCIATION
2025 Scientific Meeting
Embracing change: epidemiological methods for the future
Wednesday 16 to Friday 18 July 2025
Hotel Grand Chancellor Hobart
#AEA2025
Pre- Conference Workshops - Wednesday 16 July
Workshop Registration Fees
Workshop Registration Inclusions:-
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Admission to Workshop Session on Wednesday 16 July ONLY;
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Workshop Registration does not provide access to the AEA Conference 17-18 July;
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Morning and/or afternoon tea will be provided for Workshop Registration on Wednesday 16 July.
AEA MEMBER - Half Day $165 / 2x Half Day $225
NON - MEMBER - Half Day $290 / 2x Half Day $410
WORKSHOP 1 - Half Day Wednesday 16 July - 8:00am to 12:00pm
Title: Analysis planning for handling missing data in epidemiological studies: a new roadmap
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Description: Missing data are a common problem in epidemiological studies that can lead to bias if there is a violation in the assumptions about the causes of missing data that underlie (implicitly or explicitly) the analysis. Yet, the traditional forms of missing data assumptions (e.g. “missing at random”) are difficult to assess in practice where it is common for multiple variables to have missing data. This workshop will take participants through the steps of a new roadmap for handling missing data that is grounded in the use of causal diagrams to facilitate the specification and assessment of missingness assumptions, and thereby decide on the most appropriate approach to handle missing data.
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Prerequisites and intended audience: The target audience is epidemiologists with some statistical background, including some knowledge of regression methods.
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Presenters:
Margarita Moreno-Betancur & Ghazaleh Dashti, from the Clinical Epidemiology & Biostatistics Unit at the Murdoch Children’s Research Institute & University of Melbourne
WORKSHOP 2 - Half Day Wednesday 16 July - 1:00pm to 5:00pm
Title: Quantitative Bias Analysis with application to issues of misclassification
Description: Random error is nearly always quantified in biomedical / epidemiologic research results, while systematic error is rarely quantified. This disparate treatment exists despite the fact that systematic error often dominates the uncertainty about an estimate, and the fact that methods for quantitative bias analysis have been described for decades. Shifting point estimates to account for bias, as well as widening study intervals to account for the uncertainty due to systematic error, provides a more complete assessment of total study error and reduces the chances of inferential errors. The course will give an introduction to the available methods for the case of bias due to misclassification.
Presenter:
Dr Matthew Fox DSc
Professor, Departments of Epidemiology and Global Health, Boston University
Additional Workshop information will be added as they are confirmed.
Need Assistance?​
Contact: AEA 2025 Conference Secretariat
P: 02 6171 1312
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