Advanced Topics in Causal Research

“I like distance learning because of the interaction with a diverse, international student group of…”
Esther de Groot, Amsterdam - The Netherlands
“E-learning, as provided by Elevate, is a good opportunity to do part of the MIH on a distance.”
Tabitha Kievit, student, Tokyo - Japan

This online 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.

One particular problem in causal research is that the observed relation between a determinant and an outcome is attributed to that determinant, while in fact the observed relation should be attributed to another variable. This form of bias, often referred to as confounding, is central in this course. Other sources of bias, notably missing data and measurement error are not addressed in detail. 

Epidemiological research often focuses on quantifying the relationship between a treatment, risk factor, or exposure and health outcomes. The treatment, exposure or risk factor is often referred to as the determinant. The motive of a researcher is often to find out whether the observed relation between the determinant and the outcome is causal. This course deals with this type of research.

Learning Objectives

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

Course Deadlines

Please note that you are required to hand in assignments during some of the learning units in this course:

Week 0
Sunday before start date - introduce yourself

Week 1
Sunday – complete Learning Unit 1

Week 2
Sunday – complete Learning Unit 2

Week 3
Sunday – complete Learning Unit 3 and 4
Sunday – submit final assignment

Accreditation

As this is a university course, it is covered by academic accreditation. Upon passing the final exam, you will receive a recognized certificate from Utrecht University and the UMC Utrecht.       

Examination

To successfully complete this course, you need to actively participate in the discussion forums and complete the final assignment. The deadline for the final assignment will be announced as soon as possible. You are allowed to redo the final assignment once.

Course staff

Supervisor

Enrollment

Pick a date for this course:
(Enrollment deadline: 14 January 2019 - 23:59 CET)
113 days left.

Quick overview

  • 28 Jan 2019 – 17 Feb 2019
  • 3 weeks
  • 14 hrs/wk
  • Academic Certificate
  • 1.5 EC
  • Online learning with guidance and support
  • English
  • Weblectures, individual assignments, group assignments
  • Desktop, Laptop, Smartphone, Tablet
  • 785

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