Prospectus

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Causal inference

Course
2024-2025

Entry requirements

  • Introduction to Methodology and Statistics

  • Inferential Statistics

  • Experimental and Correlational Research (or similar courses)

Description

An important part of psychological research is discovering and explaining causal relationships. Randomised experiments form the best basis for causal inference, but experimental manipulation of the independent variable often cannot be realised for practical, ethical, or technical reasons. Therefore, causal relationships are often studied in field settings. Research in field settings varies in the amount of control that the researcher has over the study characteristics. There are true experiments in natural settings such as hospitals, schools, and factories. Other studies have a quasi-experimental design, with experimental groups, but with less control over assignment of research units to conditions. Alternatively, studies may be purely observational, without experimental interventions, but still set up in a systematic way that maximises the possibility of drawing causal conclusions (e.g. case-control-studies). In the course, we will give an overview of research designs and methods of data-analysis directed at drawing the best possible causal conclusions when the (experimental) conditions are less than ideal.

Course objectives

At the end of the course the student is able to:

  • understand and apply the core concepts, principles, and methods of causal inference in empirical research,

  • analyse and evaluate causal claims in empirical studies,

  • propose an adequate research design, given the research question or hypothesis, to prevent or remove threats to research validity, and

  • handle confounders in causal inference by computing propensity scores and using them for adjustment of causal estimates.

Timetable

For the timetable of this course please refer to MyTimetable

Registration

Education

Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register up to 5 days prior to the start of the course.

Exams

You must register for each exam in My Studymap at least 10 days before the exam date. Don’t forget! For more information, see the enrolment procedure.
You cannot take an exam without a valid registration in My Studymap.

Carefully read all information about the procedures and deadlines for registering for courses and exams.

Students who take this course as part of a LDE minor or a premaster programme, exchange students and external guest students will be informed by the education administration about the current registration procedure.

Mode of instruction

Seven 2-hour lectures and seven 2-hour mandatory workgroup sessions.

Attendance at the work group sessions is mandatory. See Brightspace for more information.

The workgroup sessions consist of case discussions, student presentations of validity threats in published empirical field studies, and data analysis for estimating treatment effects.
You should attend at least five out of seven workgroups and actively participate.

Assessment method

A written examination assesses students’ knowledge of causal inference (weight: 60% of the final grade). A short written paper assesses application of this knowledge to the validity of the conclusions of a published field study (weight: 40% of the final grade). Adequate active participation during the workgroups is an overall requirement for being awarded a final grade.

The Institute of Psychology uses fixed rules for grade calculation. It also follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. All students are required to take and pass the Scientific Integrity Test with a score of 100% in order to learn about the practice of integrity in scientific writing. Students are given access to the quiz via a module on Brightspace. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of these two policies.

Reading list

  • Rosenbaum, P. R. (2017). Observation and experiment. An introduction to causal inference. Cambridge (MA): Harvard University Press. ISBN: 9780674975576.

  • Additional papers on Brighspace.

  • Lecture slides.

Contact information

Dr. Anikó Lovik a.lovik@fsw.leidenuniv.nl