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Randomized Experimental Methods: Survey, Lab, Field and Conjoint Experiments (RSS1.14) - Closed

Experiments have become a standard part of the methodological toolkit of social scientists. In particular, they are well-suited to facilitate casual inferences. The course covers implementing, analysing, visualizing and critically evaluating such designs. In five days, course participants will have a chance to familiarize themselves with the most popular experimental approaches, namely lab, field and survey experiments.

Duration: one-week.


    Closed: registration no longer possible. We have some alternatives for you: 

    We would recommend you consider joining our course on Causal Inference with Natural Experiments: DiD, RDD, IV, and Matched Designs, which also covers several aspects relevant for experimental designs and causal inferences in social sciences. Please feel free to contact the instructor Ryan Moore (ryantmoore [at] (ryantmoore[at]hey[dot]com)) for further information. 

    We can also recommend the course on Meta-Analysis, which covers as well how to include experimental studies in meta analyses. Feel free to contact the instructor Caspar van Lissa (C.J.vanLissa [at] (C[dot]J[dot]vanLissa[at]tilburguniversity[dot]edu)) to get more information. 


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    Starting date

    17 June 2024, 9 am
    Educational method
    Main Language
    17 June 2024, 9 am - 21 June 2024, 5 pm
    Daniel Kovarek
    Unique code


    Type of education
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    See the requirements in cost and admission
    Study load (ECTS)
    Radboud Summer School

    This course offers participants an opportunity to design and program their own experiments. It provides an overview of the most popular approaches, namely lab, field, and survey experiments. It is intended for researchers who have a basic understanding of statistics and quantitative methods but have not designed and/or fielded their own experiment yet. The course will cover theoretical foundations and practicalities of experiments, placing special emphasis on design choices (external and internal validity). The instructor will also illustrate some of the typical modelling approaches using data from his own experiments, as well as publicly available replication data. He will also offer some pointers on common approaches to visualize experimental data. 
    Participants will have the opportunity to acquire the skills needed to randomize questionnaire blocks or items in Qualtrics. They will also familiarize themselves with access panels and online marketplaces (Lucid, MTurk, Prolific, etc.) where the bulk of survey experiments are fielded, critically comparing aspects such as data quality, accessibility, and cost efficiency. 
    One day will be dedicated to conjoint experiments, a versatile form of survey experiments with growing popularity, given their cost efficiency and ability to approximate real-world decision making while limiting social desirability bias. We also cover considerations of research ethics and best practices for debriefing experimental subjects when deceptive research designs are used. To avoid underreporting of outcome variables and experimental manipulations, pre-registration of experimental studies have become the norm. The course will teach you how to pre-register your future study and present best practices for pre-analysis plans (PAPs).

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    Daniel Kovarek

    Daniel Kovarek is a Postdoctoral Research Fellow at the European University Institute, at the Robert Schuman Centre for Advanced Studies. He holds a PhD in Political Science from the Central European University. He studies political behaviour at the voter and the elite level; his expertise lies in the intersection of political geography and distributive politics. Daniel has extensive experience in designing, fielding, and analysing lab, field and survey experiments. For his dissertation research, he utilized vignette and conjoint experiments to study friends-and-neighbours voting; in his current position, he studies the policy-making processes in various crises of the European Union, using survey experiments and text-as-data methods. Previously, Daniel has been teaching a wide variety of graduate-level courses on quantitative methods, applied statistics, programming, research design, as well as comparative politics. His research has appeared in Research & Politics, The ANNALS of the American Academy of Political and Social Science and Environmental Politics, among others.


    • Regular: €1049 (application deadline 1st of May)
    • Student & PhD's: €699 (application deadline 1st of May)

    Includes: your course, short morning and late afternoon courses, coffee and tea during breaks, a warm lunch every day, Official Opening, MethodsNET Café (including some drinks and snacks) Official Closing (with some drinks and snacks) and a 1-year (2024 calendar year) free membership as MethodsNET regular member.

    Excludes: transport, accommodation, social events and other costs. 

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    Level of participant: 

    • Master
    • PhD
    • Postdoc
    • Professional

    Admission requirements: 

    Some experience with inferential statistics; basic understanding of quantitative research and concepts of causal inference. Ideally, prospective participants have conducted some analyses (e.g., regression analysis, comparing means, etc.) on observational data in the past. Familiarity with statistical software (R, STATA, etc.) for conducting analyses on experimental data is helpful but not a requirement.

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