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, you'll should be able to:
- understand the concept of confounding
- understand 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
- understand 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
- understand the usefulness of sensitivity analysis to estimate the impact of unmeasured confounding, and is able to apply these methods in a computer practice
- understand the concept of effect modification
- understand the difference between 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
- understand the different ways to present effect modification in a paper and can derive information on effect modification from published studies
- understand the difference between effect modification and confounding
Nienke Verdonk MSc MA
Nienke Verdonk works as an e-learning developer at Elevate. She has a Master’s degree in educational sciences and develops the didactical elements of Elevate’s courses. You can contact Nienke for educational consultancy and the educational development of (new) courses.