SYLLABUS E-mail: littvayl@ceu.edu Mobile: +36 70 538-3683 (only call between 11am and 11pm Central European Time) Class: Tuesdays 15:30 17:10 @ FT 908 Office Hours: Tuesdays at 13:30 to 15:00 and Wednesdays at 15:15 to 16:45 and/or by appointment. (Appointment is always required 48 hours before meeting or you can t expect me to be there. Email me, call me, Tweet, etc.) Summary Experimental approaches, while always popular in psychology and the natural sciences, are also fast becoming mainstream within political science. When done correctly, they are billed to facilitate true causal inferences. For this reason they are a popular technique in the world of policy assessment and in testing political science theories. (The foundations of experimental design will be covered extensively in the quantitative introductory courses in the fall.) This class will focus on the various forms of experimental research in political science. This class is optional and it may be more work than what you would expect from a 2 credit class (4 ECTS credits). Consider this before you sign up. In addition to the assigned texts I expect you to be consulting most, if not all the reference texts listed in the syllabus for the materials that correspond to what we cover each week. (These are not itemized in the schedule. Find it.) Prerequisites for the Class The class is open to both MA and PhD students (of any CEU department) as long as their prior statistical training is adequate. Applied Stats and Multivariate are desirable but not essential. Also, it is a good idea to listen to all Freakonomics Radio episodes (except rebroadcasts) before the start of the class. Find them here: http://freakonomics.com/radio/ Auditors will have to do all assigned work (including the presentation) and will have to perform on all criteria to acceptable level to receive a passing mark. Auditors will not have to write a final paper. No dropping of the class or changes from grade to audit will be allowed after the close of registration period. I will only consider requests to change from audit to grade. Learning Outcomes The course covers both inductive and deductive form of experimental models. It is designed to advance scholar s ability to comprehend and critique articles using political science experiments and to apply these approaches in research. Throughout the course students use computer software (R) for conducting statistical analysis for their own experiments. Understanding and application of the aforementioned are applied autonomously in a creative way. The course advances the scholar s ability to contribute to the development of political science in their home countries by applying the learned approaches to analysis of their home countries (or any other place for that matter) by acquiring cutting-edge approaches of experimental research. Since experiments come from outside of political science, the scholars emerged in the course will acquire the ability to expand both their own and their field s horizons by extending the their inferential understanding beyond the boundaries of the discipline. Inference based on an experimental design is universal in all of empirical sciences and therefore this course will certainly expand the scholar s view into an interdisciplinary vision of the world. The course will expand the scholar s ability to design, implement and write up a good quality research in a thorough, rigorous and consistent manner. The experiments covered by the course advance the scholar s ability even going beyond writing research proposals and formulating research questions. The course will help students conduct actual empirical research. The final paper (article) for the course is designed to advance the student in mastery of academic writing style and argumentation in English: ability to use English grammar, vocabulary and style appropriate for written academic products and ability to construct 1
academic arguments. And in this final paper (and also in other components of the course) we will use graphs and other visual communication of results. In writing and also sharing the findings of the final paper students will advance their ability to synthesize information, determine a focus point, discern the main line of argumentation and orally present these. Their ability to generate logical, plausible and persuasive arguments, connect, compare and contrast, ability to identify logical relations and mistakes of arguments, ability to make appropriate analytical distinctions, (and etc.) will be advanced through the course. Through this both students higher order thinking (such as to seeing patterns and generalizing from facts) reasoned judgment will grow. Special emphasis is placed on responsible research conduct and issues of research ethics showing students appropriate and inappropriate academic behavior. Evaluation of Student Work Participation (engagement in class): 10% Weekly Discussion Notes and Additional Assignments: 25% Weekly Forum Activity: 15% Presentation of Experimental Design (March 22, 19:30): 20% Publishable Article (not required for auditors): 30% On a 100 point scale, the grading would be as follows: A 94.00 100 A- 87.00 93.99 B+ 80.00 86.99 B 73.00 79.99 B- 66.00 72.99 C+ 59.00 65.99 Participation (engagement in class). It is an absolute requirement that you come to class, you stay engaged in class and that you come to class prepared. If you will miss a class or come late for any reason, make sure I am notified before the class. Weekly Discussion Notes and Additional Assignments: Weekly assignments include producing discussion points for class. I don t need a complete essay just a sentence or two for each discussion point. Please produce several for each reading that was assigned. Make them original and interesting. I ll be looking to see if you have read and thought about the readings. Also, for participation, I will be looking to see if you brought up these points and how good these points were. You need to submit these discussion points by 9am before class. I may assign other things in class. This includes the Course on Research Ethics (CORE) that is mandatory for everyone and due to second week of class. Course can be found here (CEU is a member and CORE is mandatory for anyone doing human subject research.) http://www.ethics.gc.ca/eng/education/tutorialdidacticiel All assignments are weighted equally. Lowest grade is dropped. Weekly Forum Activity: Every week I will assign a podcast to listen to. We will start an online discussion forum for these podcasts. You will need to write your post (150-250 words) before you can see others. Once you posted, you should discuss with your classmates. Your initial post will always be due on Thursday and you should make comments on other people s posts by Saturday. Intellectual level of your contribution will be graded (for both your initial post and the discussion). Presentation of Experimental Design (March 22, 19:30): Mark your calendar NOW! Everyone will have to present their individual experimental project (design AND preliminary analysis) at this occasion. You cannot skip it. Presentations cannot exceed 8 minutes but have to include all key aspects and preliminary results of your experiment. (I will be strict on time.) Needless to say, you will need to arrange your life in a way that you have completed your experiment and have results by this occasion. Note that from Feb 23 to March 8 you will be workshopping your ideas for this project. But it is a good idea to develop ideas for these occasion before Feb 23. Publishable Article (not required for auditors): Your final paper will have to include original research using one of the methodologies covered in class. It has to be of publishable quality 2
adhering to the submission guidelines of Science or Nature. Your pick. The manuscript will have to be appropriately anonymized if this is required by the journal only identifying you via the file name. Since the journal asks for multiple files, ignore this request. Merge the multiple PDFs into one. Your data collection methodology can be either through social media or students in your home country. I will not judge the paper by the quality of the sample or the findings. More on the design and the idea behind the design. This will be a first pilot before we spend money on a better sample, still it has to be written up as if it was the final result. Important Notice Complete academic honesty is expected of everyone. Failure to comply with this requirement will result in automatic failure in this course (and subsequently in the program) and additional disciplinary action on higher levels. This is an American university and American standards will be applied. For more information about these standards see: http://en.wikipedia.org/wiki/ Academic dishonesty (READ VERY CAREFULLY!) All assignments are to be done individually. You can talk about how to do it, but none of the actual work can be done in a group. Any evidence to the contrary will be investigated. REGULAR CLASS SCHEDULE Week Topic Required Readings* Jan 12 History & Intro CORE Training, Salsburg (2002) Chapters 1 & 5 Kahneman & Tversky (1979), McDermott (2002) Jan 19 Lab Experiments Dawes et al (2007), Oxley et al (2008), Iacoboni & Schreiber (2012), Aarøe & Petersen (2013) Jan 26 Survey Experiments Johnston (1992), Arceneaux & Nicholson (2012) Gaines et al (2007), Coutts & Jann (2011) Feb 2 Field Experiments Gerber & Green (2000), Bond et al (2012), LaCour and Green (2015), Broockman & Kalla (2015) Feb 9 Natural Experiments Lassen (2005), Sekhon & Titiunik (2012), Keele & Titiunik (2015) Feb 16 Quasi Experimental Design Broockman (2009), Lyall (2010), Green & Sovey (2011) Arceneaux et al (2006) Feb 23 Workshop Mar 1 Workshop w/ Fede Vegetti Special Academic Transparency Assignment Due Mar 8 Amazon Mechanical Turk Berinsky et al (2012), New Platform Maybe (Crowdflower?) Mar 15 National Holiday Class Canceled Mar 22 Transparency Bem (2011), Franco et al (2014), Franco et al (2015) PS Special Issue (47:1) on Openness in Political Science Alvarez (2014) Blog Post on Oxford University Press ALSO 19:30 Presentations Going late!! Mar 29 Ethics Gerber et al (2008), Fujii (2012), Broockman & Kalla (2014) also Google and read about the Stanford & Dartmouth Montana Field Experiment Reference Texts Druckman, James N., Green, Donald P., Kuklinski, James H., Lupia, Arthur. Cambridge Handbook of Experimental Political Science. Cambridge: Cambridge University Press, 2011. Kittel, Bernhard, Luhan, Wolfgang J., Morton, Rebecca B.. Experimental Political Science: Principles and Practices. London: Palgrave Macmillan, 2012. Morton, Rebecca B. and Williams, Kenneth C.. Experimental Political Science and the Study of Causality: From Nature to the Lab. Cambridge: Cambridge University Press, 2010. 3
Articles Aarøe, Lene and Michael Bang Petersen. Hunger Games: Fluctuations in Blood Glucose Levels Influence Support for Social Welfare. Psychological Science 24(12) (December 2013): 2550-2556 Alvarez, R. Michael. The Pros and Cons of Research Preregistration. Political Analysis Published Online: Sep 2014 Arceneaux, Kevin, Alan S. Gerber and Donald P. Green. Comparing Experimental and Matching Methods Using a Large-Scale Voter Mobilization Experiment. Political Analysis 14 (Winter 2006): 37-62 Arceneaux, Kevin and Stephen P. Nicholson. Who Wants to Have a Tea Party? The Who, What, and Why of the Tea Party Movement. PS: Political Science and Politics 45(4) (October 2012): 700-710 Bem, Daryl J.. Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect. Journal of Personality and Social Psychology 100 (Mar 2011): 407-425 Berisnky, Adam J., Gregory A. Huber, Gabriel S. Lenz. Evaluating Online Labor Markets for Experimental Research: Amazon.com s Mechanical Turk Political Analysis 20(3) (Summer 2012): 351-368 Bond, Robert M., Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle and James H. Fowler. A 61-million-person Experiment in Social Influence and Political Mobilization. Nature 489 (Sep 2012): 295-298 Broockman, David E.. Do Congressional Candidates Have Reserse Coattails? Evidence from a Regression Discontinuity Design. Political Analysis 17(4) (2009): 418-434 Broockman, David E. and Joshua Kalla. Irregularities in LaCour(2014). (May 2015) Broockman, David E. and Joshua L. Kalla. Campaign Contributions Facilitate Access to Congressional Officials: A Randomized Fiel Experiment. American Journal of Political Science Early View: 2 April 2015 Coutts, Elisabeth and Ben Jann. Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT). Sociological Methods & Research 40(1) (2011): 169-193. Dawes, Christopher T., James H. Fowler, Tim Johnson, Richard McElreath and Oleg Smirnov. Egalitarian Motives in Humans Nature 446 (April 2007): 794-796 Franco, Annie, Neil Malhotra and Gabor Simonovits. Publication Bias in the Social Sciences: Unlocking the File Drawer. Science 345 (Sep 2014): 1502-1505 Franco, Annie, Neil Malhotra and Gabor Simonovits. Underreporting in Political Science Survey Experiments: Comparing Questionnaires to Published Results. Political Analysis 23 (Spring 2015): 306-312 Fujii, Lee Ann. Research Ethics 101: Dilemmas and Responsibilities. PS: Political Science and Politics 45(4) (Oct 2012): 717-723 Gaines, Brian J., James H. Kuklinski and Paul J. Quirk. The Logic of the Survey Experiment Reexamined. Political Analysis 15 (2007): 1-20 Gerber, Alan S. and Donald P. Green. The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment American Political Science Review 94(3) (Sep 2000): 653-663 Gerber, Alan S., Donald P. Green and Christopher W. Larimer. Social Pressure and Voter Turnout: Evidence from a Large-scale Field Experiment. American Political Science Review 102(1) (February 2008): 33-48 4
Green, Donald P. and Allison J. Sovey. Instrumental Variables Estimation in Political Science: A Reades Guide. American Journal of Political Science 55 (January 2011): 188-200 Iacoboni, Marco and Darren Schreiber. Huxtables on the Brain: An fmri Study of Race and Norm Violation Political Psychology 33 (June 2012): 313-330 Johnston, Richard. Party Identification Measures in the Anglo-American Democracies: A National Survey Experiment. American Journal of Political Science 36 (May 1992): 542-559 Kahneman, Daniel and Amos Tversky. Prospect Theory: An Analysis of Decision under Risk Econometrica 47 (2)(March 1979): 263-291 Keele, Luke and Rocio Titiunik. Natural Experiments Based on Geography. Political Science Research and Methods Published Online: April 2015 LaCour, Michael J. and Donald P. Green. When Contact Changes Minds: An Experiment on Transmission of Support for Gay Equality. Science 346 (Dec 2014): 1366-1369 Lassen, David Dreyer. The Effect of Information on Voter Turnout: Evidence from a Natural Experiment American Journal of Political Science 49(1) (January 2005): 103-118 Lyall, Jason. Are Coethics More Effective Counterinsurgents? Evidence from the Second Chechen War. American Political Science Review 104(1) (February 2010): 1-20 McDermott, Rose. Experimental Methods in Political Science. Annual Review of Political Science 5 (2002): 31-61 Oxley, Douglas R., Kevin B. Smith, John R. Alford, Matthew V. Hibbing, Jennifer L. Miller. Political Attitudes Vary with Physiological Traits University of Nebraska - Lincoln Faculty Publications: Political Science paper 26 (2008) Salsburg, David. The Lady Testing Tea: How Statistics Revolutionized Science in the Twentieth Century. New York: Henry Holt and Company, 2002. Chapters 1 and 5. Sekhon, Jasjeet S. and Rocio Titiunik. When Natural Experiments are Neither Natural nor Experiments. American Political Science Review 106(1) (Feb 2012): 35-57 PS Special Issue (47:1) on Openness in Political Science [1] Lupia, Arthur and Colin Elman. Openness in Political Science: Data Access and Research Transparency - Introduction PS: Political Science and Politics 47(1) (January 2014): 19-42 [2] Elman, Colin and Diana KKapiszewski. Data Access and Research Transparency in the Quanlitative Tradition PS: Political Science and Politics 47(1) (January 2014): 43-47 [3] Moravcsik, Andrew. Transparency: The Revolution in Qualitative Research PS: Political Science and Politics 47(1) (January 2014): 48-53 [4] Lupia, Arthur and George Alter. Data Access and Research Transparency in the Quantitative Tradition PS: Political Science and Politics 47(1) (January 2014): 54-59 [5] Dafoe, Allan. Science Deserves Better: The Imperative to Share Complete Replication Files PS: Political Science and Politics 47(1) (January 2014): 60-66 [6] McDermott, Rose. Research Transparency and Data Archiving for Experiments PS: Political Science and Politics 47(1) (January 2014): 67-71 [7] Carsey, Thomas M.. Making DA-RT a Reality PS: Political Science and Politics 47(1) (January 2014): 72-77 [8] Ishiyama, John. Replication, Research Transparency, and Journal Publications: Individualism, COmmunity Models, and the Future of Replication Studies PS: Political Science and Politics 47(1) (January 2014): 78-83 5