Advanced Methods in Epidemiology and Biostatistics
This course provides an in-depth introduction to advanced methodological approaches in epidemiology and biostatistics, with a particular focus on register-based research. The course is being held in Forskningens Hus, Aalborg.
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Location
Auditorie A, Forskningens Hus, Søndre Skovvej 15, 9000 Aalborg
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Using examples primarily drawn from large-scale health registries, participants will gain practical insight into contemporary statistical tools and epidemiological designs, such as pseudo-observations, self-controlled designs, and target pipelines for handling data.
The course combines methodological lectures with applied case discussions, highlighting common pitfalls and best practices in epidemiological research.
Programme
Learning Objectives
The overall aim of the course is to give participants insight into advanced tools and concepts in epidemiology and biostatistics, with a focus on addressing bias, confounding, and complex causal inference in register-based research. Participants will gain deeper insight into modern techniques for strengthening the validity of observational studies.
After completing the course, participants will be able to:
- Understand and critically evaluate advanced epidemiological and biostatistical methods used in observational research
- Apply pseudo-observations in survival analysis to estimate complex parameters
- Explain and assess self-controlled case-series designs and their assumptions
- Identify and mitigate common sources of bias and confounding in register-based studies
- Use efficient workflows for handling large-scale registry data, including tools available at Statistics Denmark
- Critically assess epidemiological studies with respect to design, analysis, and interpretation
Target Group
- PhD students in epidemiology, biostatistics, public health, medicine, or related fields.
- Early-career researchers working with observational or register-based data.
Participants are expected to have basic prior knowledge of epidemiology and statistical methods (e.g., regression models and survival analysis).
Course Format
The course consists of lectures, software demonstrations, and case-based discussions. Emphasis is placed on real-world examples from cardiovascular and population-based research, with opportunities for interaction and discussion throughout the day.