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Conferences and seminars

Advanced Experimental Methods and Panel Design for the Social Sciences


This is a two-day workshop led by Professor Diana C. Mutz (University of Pennsylvania), a leading scholar in experimental political science. The workshop will introduce and discuss advanced experimental techniques, and panel designs relevant for survey-based social science research. The workshop is physically in Bergen, and open to participants from all KODEM-affiliated institutions.

is Samuel A. Stouffer Professor of Political Science and Communication, University of Pennsylvania, Director, Institute for the Study of Citizens and Politics (ISCAP).

Mutz is also part of the International Scientific Advisory Board for KODEM.

This is a two-day workshop at the University of Bergen. The workshop will introduce and discuss advanced experimental and panel analysis techniques being used to advance experimental and survey research in the social sciences. The emphasis will be on improving research designs through deeper understanding of how we are partitioning variance using various experimental and panel approaches. Day 1 will include lectures covering common pitfalls in experimental design and analyses, making the most of within-subject/repeated measures designs, panel design and analysis techniques that take advantage of their unique strengths. Day 2 will provide participants with the opportunity to present and receive feedback on their research designs, offering a unique opportunity for tailored methodological advice. The workshop is open to participants from the University of Bergen and other KODEM-affiliated institutions. Please register before 22 April by .

ÌýThe workshop is free of charge, but participants must cover their own travel, food and accommodation. All participants will be invited to a joint dinner on Day 1.Ìý

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Recommended readings will be found in the fact box below. This will not be statistics lectures, but on understanding larger conceptual issues in research design.

Program

Day 1:

  • 08:30-09:00: Arrival and registration
  • 09:00-09:30: Welcome and presentation
  • 09:30-10:30: Session 1: Common pitfalls: Getting the most out of your original experiment
  • 10:45-11:45: Session 2: Within-subjects/repeated measures experimental designs
  • 11:45-13:15: Lunch break
  • 13:15-14:15: Session 3: The Unique Strengths of Panel Designs 
  • 14:45-16:00: Session 4: Best Practices for analyzing individual-level panel data 

 

Day 2:

  • 09:00-15:00, three sessions

Recommended readings

Problematic Issues in Contemporary Experiments:

Westwood, S.J., 2025. The potential existential threat of large language models to online survey research. Proceedings of the National Academy of Sciences, 122(47), p.e2518075122.

Mutz, D.C., Pemantle, R. and Pham, P., 2019. The perils of balance testing in experimental design: Messy analyses of clean data. The American Statistician, 73(1), pp.32-42.

Mutz, Diana C. 2021. Improving Experimental Treatments in Political Science. Chapter 12 in James Druckman and D.P. Green, (Eds.), Advances in Experimental Political Science (Cambridge University Press), pp. 219.

 

Within-Subjects Experimental Design:

Stephen G. West & Jeremy C. Biesanz & Oi-Man Kwok. 2008. Within-Subject and Longitudinal Experiments: Design and Analysis Issues. Chapter 13 in SAGE Handbook of Methods in Social Psychology (C. Sansone, C. C. Morf & A. T. Panter (eds.).

Clifford, Scott et al. 2021. Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments. American Political Science Review (2021) 115, 3, 1048–1065.

Bansak, Kirk, Jens Hainmueller, Daniel J. Hopkins, and Teppei Yamamoto. Xxxx. Conjoint Survey Experiments. Chapter 2 in James Druckman and Donald P. Green, (Eds.), Advances in Experimental Political Science (Cambridge University Press), pp. 257-270.

 

Panel Analyses:

Allison, Paul D. 2009. Fixed Effects Regression Models. SAGE Series: Quantitative Applications in the Social Sciences.

Vaisey, S. and Miles, A., 2017. What you can—and can’t—do with three-wave panel data. Sociological Methods & Research, 46(1), pp.44-67.

Allison, P.D., Williams, R. and Moral-Benito, E., 2017. Maximum likelihood for cross-lagged panel models with fixed effects. Socius, 3, p.2378023117710578.

Bellemare, M.F., Masaki, T. and Pepinsky, T.B., 2017. Lagged explanatory variables and the estimation of causal effect. The Journal of Politics, 79(3), pp.949-963.