Dr Matteo M Galizzi

Dr Dario Krpan

Dr Yana Litovsky

Dr Alina Velias

This course is compulsory on the Executive MSc in Behavioural Science. This course is not available as an outside option to students on other programmes.

Behavioural science is the scientific study of human behaviour, and it combines research techniques from experimental psychology and economics. The course offers an integrated training in advanced behavioural science methods by introducing students to state-of-the-art experimental techniques that stretch across the spectrum of both disciplines. The course covers the following topics: an overview and brief history of research methods in behavioural science; advanced considerations in experimental design; principles of survey design; replicability of experiments; open, transparent, and reproducible behavioural science; determining evidential value of behavioural science research: undisclosed flexibility in data collection, dance of p-values, p-curve analysis; pre-registration, pre-analysis plan; reproducibility practices in modern behavioural science experiments; measuring attitudes and preferences; designing behavioural priming experiments and measures that tap into implicit cognition; behavioural game theory and experimental games of strategic interaction; statistical modelling and non-linear regression models; understanding the mechanisms behind behavioural effects by employing experimental-causal-chain, measurement-of-mediation, and moderation-of-process designs; principles of survey design; simple physiological research techniques; tests of hypotheses and sample size calculations for experiments in theory and practice; systematic reviews of the literature.

The course is delivered through a combination of lectures and seminars totalling a minimum of 20 hours in the third teaching session (April).

Proposal (100%).

For the formative assignment, you will need to produce a short proposal (max 500 words) that will briefly explain how you would like to organise and structure your summative assignment.

• Angrist, J.D., Pischke J-S. (2015). Mastering ‘Metrics: the Path from Cause to Effect. Princeton: Princeton University Press.
• Camerer, C.F. (2003). Behavioral Game Theory: Experiments in Strategic Interaction. Princeton: Princeton University Press.
• Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019). Failing Grade: 89% of Introduction-to-Psychology Textbooks That Define or Explain Statistical Significance Do So Incorrectly. Advances in Methods and Practices in Psychological Science, 2, 233-239.
• Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publication.
• Dijksterhuis, A., Chartrand, T. L., & Aarts, H. (2007). Effects of Priming and Perception on Social Behavior and Goal Pursuit. In J. A. Bargh, J. A. Bargh (Eds.), Social psychology and the unconscious: The automaticity of higher mental processes (pp. 51-131). New York, NY, US: Psychology Press.)
• Förster, J., & Liberman, N. (2007). Knowledge activation. Social psychology: Handbook of basic principles, 2, 201-231.
• Gawronski, B., & De Houwer, J. (2014). Implicit measures in social and personality psychology. Handbook of research methods in social and personality psychology, 2, 283-310.
• Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.
• Harrison, G.W., List, J.A. (2004). Field experiments. Journal of Economic Literature, XLII, 1009-1055.
• Miguel, E., Camerer, C.F., Casey, K., Cohen, J., Esterling, K.M., Gerber, A., Glennerster, R., Green, D.P., Humphreys, M., Imbens, G., Laitin, D., Madon, T., Nelson, L., Nosek, B.A., Petersen, M., Sedlmayr, R., Simmons, J.P., Simonsohn, U., & Van der Laan, M. (2014). Promoting transparency in social science research. Science, 343(6166), 30-31.
• Mitchell, M.N. (2015). Stata for the Behavioural Sciences. Stata Press.
• Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., & the PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement. Annals of Internal Medicine, 151(4), 264-269.
• Munafò, M.R., Nosek, B., Bishop, D.V.M., Button, K.S., Chambers, C.D., Percie Du Sert, N., Simonsohn, U., Wagenmakers, E.J., Ware, J.J., & Ioannidis, J.P.A. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1(1), 0021. 
• Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014). P-curve: a key to the file-drawer. Journal of Experimental Psychology: General, 143(2), 534-547
• Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89, 845-851.
• van't Veer, A. E., & Giner-Sorolla, R. (2016). Pre-registration in social psychology—A discussion and suggested template. Journal of Experimental Social Psychology, 67, 2-12.
• Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological science, 22(11), 1359-1366.
• Stantcheva S. (2023). How to run surveys: a guide to creating your own identifying variation and revealing the invisible. Annual Review of Economics, 15, 205-234.

Proposal (100%).

For the summative assignment, you will be required to expand the research proposal plan submitted as part of the formative assignment into a full research proposal comprising 3,000 words.

Your task will be to propose a design and implementation of a behavioural science experiment potentially entailing the use of different software packages or online resources introduced in the seminars. The structure of the proposal should be as follows:

• Introduce a viable research question (on a topic of your choice) that will guide your experimentation
• Describe how you would design and implement behavioural science research to answer the question; and
• Explain which approaches covered in lectures and seminars you would use to collect, analyse, and interpret the data.

In the proposal, we will expect you to use in-text scholarly citations and provide a reference list at the end. The summative assignment should allow you to not only demonstrate your knowledge regarding the present course, but also to gain deeper insights into experimental analysis and design that should help you in producing a high-quality dissertation. Teaching staff will have the option of randomly reviewing 10% of the submissions via a quick oral examination online to check students' understanding.