MEDFL5580 – Epidemiological methods, beyond the basics

Course content

The course introduces causal graphs (DAGs) and modern designs in epidemiology. It also introduces multilevel analysis and will give a user oriented introduction to handling of missing data (by multiple imputation) in Stata. It also covers the use of splines to handle non-linearity in regressions.

Learning outcome

The course has five main subjects:

  • Causal graphs (DAGs)
  • Modern Designs
  • Multiple Imputation
  • Splines in regressions
  • Multilevel models

Also included are three minor subjects:

  • Interaction
  • Register epidemiology
  • An introduction to Stata

Causal graphs introduce Directed Acyclic Graphs (DAGs) and will show examples of their use in medical research. DAGs are useful tools for understanding confounding, mediation and selection bias. A DAG analysis shows variables that should be adjusted for, and variables that should not be adjusted for.

The Design part will review classic research designs; cross sectional, cohort and case control. Focus will be on more advanced designs such as nested case control, case cohort and cross over designs. Strengths and weaknesses of the different designs will be discussed and examples of the different designs presented.

Multiple imputation: The lecture gives a short introduction to different missing-data mechanisms and how to handle missing data. The focus will b