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Causal Inference, Part II: Drawing Causal Conclusions from Epidemiological Studies
Provider: Faculty of Health and Medical Sciences

Activity no.: 3327-20-00-00 
Enrollment deadline: 01/10/2020
Date and time23.11.2020, at: 08:30 - 27.11.2020, at: 15:00
Regular seats25
Course fee3,360.00 kr.
LecturersNaja Hulvej Rod
ECTS credits2.90
Contact personKathe Jensen    E-mail address: kje@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: fak-phdkursus@sund.ku.dk

Aim and content
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee.


Learning objectives
A student who has met the objectives of the course will be able to:
• Identify causal questions and demonstrate a critical understanding of the assumptions underlying causal conclusions in epidemiology

• Understand the basic notation and models used in the causal inference literature

• Identify study designs (e.g. the emulated trial approach, negative controls, instrument variable approach), which may improve possibilities for drawing causal inference in epidemiology.

• Understand when an Instrumental Variables (IV) analysis is appropriate and which assumptions such an analysis relies on.

• Conduct mediation analysis using the medflex R-package. This will cover linear as well as non-linear models.

• Integrate results from several different approaches, where each approach has
different independent key sources of potential bias, i.e. triangulation.


Content
Epidemiologists and public Health scientists routinely ask causal questions such as “Does smoking cause breast cancer?” “Does maternal thyroid disorder increase the risk of cerebral palsy?” This course gives an applied introduction to modern methods of causal inference that may help answer such questions.

The course covers a general discussion on how to phrase causal questions and critically evaluate the underlying assumptions. It also provides a range of tools to address causality including various study designs (e.g. emulated trials, negative controls, instrument variables). The instrumental variable (IV) design, for instance genetic instruments in the case of Mendelian Randomization, allows the researcher to test the hypothesis of no exposure effect, and under some further assumptions also allows an estimation of a causal exposure effect even in the situation of unmeasured confounding.

The course covers classical IV-techniques and discusses the assumptions underlying the popular IV analysis. The course also covers mediation analysis that focuses on breaking down a given exposure effect into different causal pathways. The principal example of such a strategy is the decomposition of the total effect into an indirect effect mediated through a specific mediator and the remaining direct effect.

Finally, the course looks into different ways of integrate results from several different approaches, where each approach has different independent key sources of potential bias, also called triangulation.

Note: There is a Part I of this course which introduces basic concepts in causal inference: Inverse probability Weighting and G-Estimation


Participants
The course is aimed at PhD students in Public Health and Epidemiology. There will be a maximum of 25 students. Participants are expected to have basic epidemiological skills and be numerate. Basic knowledge on the methods of Directed Acyclic Graphs (DAGs), Inverse probability Weighting and G-Estimation is a perquisite for this course.


Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

Public Health and Epidemiology
Biostatistics and Bioinformatics
All graduate programmes


Language
English


Form
The course will include a combination of lectures, group work, discussions, and individual exercises.


Course director
Naja Hulvej Rod, Professor, Department of Public Health, University of Copenhagen, nahuro@sund.ku.dk


Teachers
Katrine Strandberg-Larsen, Associate Professor, Section of Epidemiology, Department of Public Health, University of Copenhagen

Torben Martinussen, Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen

Theis Lange, Associate Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen

Long Nguyen, Assistant Professor, Section of Epidemiology, Department of Public Health, University of Copenhagen


Dates
23 – 27 November 2020


Course location
Center for Sundhed og Samfund (CSS)


Registration
Please register before 1 October 2020

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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