Advanced Epidemiologic Methods: Causal Research and prediction modelling

Veranstaltung 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

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