Ausschließlich für Fachpublikum
Intensive Short Course
Learning objectives of this intensive short course
By the end of this week, participants should be able to:
- Critically assess the results of epidemiological studies on causal relationships or prediction models
- Correctly define exposures and learn how to best represent them in models
- Understand difference between various sources of bias (confounding, measurement error and missing data) and the way these biases may differentially affect studies on causal relationships and prediction models.
- Describe key assumptions of methods used to control for (time-varying) confounding.
- Describe key assumptions of methods used to handle missing observations.
- Understand the reasons for and consequences of overfitting prediction models
- Describe recent developments in the fields of causal research and prediction modelling
Rolf H.H. Groenwold, Leiden University Medical Center (NL)
Maarten van Smeden, Leiden University Medical Center (NL)
Berlin School of Public Health / Institut für Public Health
Charité Campus Virchow-Klinikum
Forum 3, Raum 3