Lecturers: Rolf H.H. Groenwold, MD, PhD, Leiden University Medical Center (NL) &
Maarten van Smeden, PhD, Leiden University Medical Center (NL)
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
Basic knowledge of epidemiology
Familiarity with R statistical software (for a short introduction see http://www.r-tutorial.nl/)
510 € for enrolled students (proof required)
Tanja Te Gude
Tel. +49 30 450 570 812