Advanced Topics in Causal Research: Confounding and Effect Modification

This course will address two important topics in causal epidemiologic research, namely confounding and effect modification. These topics will be discussed in the context of both etiologic research and observational intervention research. Effect modification and confounding are difficult concepts to understand and often mixed up. In this course the theory as well as the practical side of these issues will be discussed.

At the end of the course, the student:

• understands the concept of confounding
• understands the different methods to determine whether there is confounding and to adjust for confounding, and is able to apply these methods in a computer practice
• understands more advanced methods to adjust for confounding namely propensity score method and instrumental variable method, and is able to apply these methods in a computer practice
• understands the usefulness of sensitivity analysis to estimate the impact of unmeasured confounding, and is able to apply these methods in a computer practice
• understands the theory of the sufficient cause model
• understands the concept of effect modification on an additive and a multiplicative scale and is able to calculate effect modification, and its confidence interval, on an additive and a multiplicative scale by hand and by computer
• understands the different ways to present effect modification in a paper and can derive information on effect modification from published studies
• understands the implications of assessing effect modification on sample size calculations and multiple comparisons
• understands the difference between effect modification and confounding

Our courses are aimed at clinical researchers, nurses, general practitioners, and other health professionals who want to improve their skills in epidemiology, statistics and (clinical) research.

1 week, fulltime