Basic knowledge of R and generalized linear models
This course considers causal inference and sources of bias which may arise when answering causal questions, such as missing data, confounding, measurement error and selection bias. Topics which will be discussed in this course are: recognize different objectives of data analysis (descriptive vs. prediction vs. causal), the potential outcomes framework, experimental designs versus observational designs, directed acyclic graphs, bias in studies of causal effects, and modern computational methods in causal data analysis, in particular methods which deal with bias due to missing data (multiple imputation) and confounding (adjustment, propensity scores).
After successful completion students are able to:
Explain the differences between causal and non-causal analysis of data;
Recognize questions and situations that ask for a causal approach to data analysis;
Know the pitfalls of causal analyis, such as confounding, missing data, selection bias and measurement error observational studies.
Use modern computational approaches in causal data analysis;
Effectively communicate a causal data analysis to a multidisciplinary data science team.
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
Mode of instruction
Lectures and exercise classes
Assesment will be done with a written exam and a practical assignment. Details will be made available on Brightspace before the start of the course.
From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.