We are excited to announce the upcoming Summer Meeting of the Danish Epidemiological Society on June 2nd, 2025 in Copenhagen with a stellar line-up of Danish and international speakers.
Measurement error and information bias in epidemiological research
DES Summer meeting 2025 – Monday June 2nd, 2025
Location: Auditorium 35.01.05, City Campus (CSS), Gammeltoftsgade 15, 1355 Copenhagen.
10:00-10:30: Arrival, coffee and snacks
10:30-10:35: Introduction and welcome
10:35-12:00: Understanding measurement error in advanced epidemiology
Moderator: Stine Schramm
12:00-13:00: Lunch
13:00-14:30: Measuring gender and ethnicity
Moderator: Terese Sara Høj Jørgensen
14:30-15:00: Coffee break
15:00-15:45: 4 short talks from Society members on measurement error/information bias
Moderator: Julie Werenberg Dreier
15:45-16:00: Short break with refreshments
16:00-17:00: Methods of analysis for error-prone data
Moderator: Amalie Timmermann
17:00- : Food and drinks
The meeting is hosted together with Section of Social Medicine, Department of Public Health, UCPH
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Would you like to present your work at the DES Summer meeting June 2nd, 2025?
This year, our meeting is focused on information bias and measurement error, and we want to hear how our members work with or around these.
We are looking for epidemiologists who would like to give a short (approx. 10 min) oral presentation covering the topic of information bias or measurement error in epidemiological research. You are therefore invited to contribute to this event by submitting an abstract of your work. Four abstracts will be selected for presentations, providing an excellent opportunity to share your findings and engage with fellow epidemiologists.
Submission Guidelines:
We look forward to your contributions and to a stimulating and insightful meeting.
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Deadlines for registration: 15th of May 2025.
Participation fee for DES members:
Participation fee for non-DES members:
Questions? Please contact dansk.epidemiologisk.selskab@outlook.dk
Become a DES-member today by clicking the link below: