Admission requirements
Basic knowledge of R and generalized linear models.
Description
A key goal of data science is to help people make better decisions. For example, in health settings, the goal is to help patients and doctors decide among several possible strategies. However, one cannot learn what the best decisions are from data alone. In order know which decisions to make, we need to be able to distinguish cause from effect. This is only possible if we combine data with causal expert knowledge. By combining data with knowledge on how data were collected (i.e., design) and with known mechanisms that play a role in the collected data (i.e., the causal structure), we can use data to answer causal questions. In this course we consider how to formulate causal questions, how to design studies to answer causal questions and how to draw causal inference from data taking into account sources of bias which may arise.
Course Objectives
After successful completion students are able to:
- Explain the differences between causal and non-causal analysis of data and recognize questions and situations that ask for a causal approach to data analysis;
- Formulate a causal question of interest using the potential outcomes framework;
- Formulate an observational or experimental study design to answer a causal question for a given situation;
- Assess whether in a given application the causal assumptions hold that are needed to identify a causal effect and visualize such assumptions using directed acyclic graphs;
- Identify which of the discussed computational methods in this course (such as outcome regression, inverse probability weighting, multiple imputation) give valid causal inference in a new practical situation, apply the methods and draw valid conclusions;
- Create a report in which a causal data analysis is explained to a multidisciplinary data science team, including motivation and evaluation of the causal assumptions and interpretation of results.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of Instruction
Lectures, exercises and assignments.
Assessment method
This course has an individual exam, and a group assignment. The final grade will be determined as a weighted average of the group assignment (30%) and the (retake) exam (70%). Both the grade of the assignment and the exam should be at least 5.5.
If the grade of the assignment is lower than 5.5, the assignment can be improved, but the final grade of the assignment cannot become higher than 5.5.
Partial grades cannot be carried over to the next academic year, the grade of the group assignment and the grade of the exam should be obtained within the same year.
Reading list
The list of literature will be posted on Brightspace.
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
S.le_cessie@lumc.nl
Remarks
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.