|Course coordinator(s)||prof. dr. ir. EJM Feskens|
|Lecturer(s)||prof. dr. ir. P van 't Veer|
|prof. dr. HC Boshuizen|
|prof. dr. ir. EJM Feskens|
|Examiner(s)||prof. dr. ir. EJM Feskens|
Language of instruction:
Assumed knowledge on:
Introduction to Epidemiology and Public Health, Basic and Advanced statistics, Study Designs, Analytical Epidemiology I
MSc thesis with a focus on nutritional or public health epidemiology
This course introduces advanced state-of-the-art topics in (nutritional) epidemiology and prepares for a thesis or internship in this field.
Course topics include:
- causal Thinking and etiologic research versus prediction and data science;
- dose-response analyses using splines;
- dealing with missing values including multiple imputation;
- advanced analysis of confounding including DAGs;
- advanced analysis of effect modification;
- meta-analysis including meta-regression.
Note: this advanced course is currently under development, topics may be included or replaced according to recent developments in the field, to reflect the state of the art in nutritional epidemiology.
Note: This course is in part based on the course HNH-30806 Analytical Epidemiology that was offered until the 2018/2019 academic year. When you attended that course and also want to take this course, please consult your study adviser.
After successful completion of this course students are expected to be able to analyse data of observational studies and apply advanced methods, in order to do this they will learn:
- to understand the distinction between epidemiology and data science, and between etiologic versus predictive modelling;
- to understand and apply directed acyclic graphs (DAGs) to identify a minimal set of confounders in observational studies and interventions;
- to apply and interpret models on multiplicative and additive interactions;
- to apply and interpret methods for dose-response analyses including splines;
- to apply and interpret methods for dealing with missing values incl. multiple imputations:
- to execute and interpret meta-analysis;
- to design a protocol for data analysis and execute the data analysis according to the protocol.
All data analyses will be executed in R and in this way students will implicitly learn how to use R for (nutritional) epidemiology and data analysis.
Lectures, e-modules, literature study, data analysis practicals and (individual and/or group) assignments.
As this is a new course, the assessment strategy and method will be elaborated in the course guide.
To be announced.
|Verplicht voor:||MNH||Nutrition and Health||MSc||A: Nutritional and Public Health Epidemiology||6MO|