Experimental Methods for Behavioral Science

Prerequisites (knowledge of topic)
Each student is to submit an outline (no more than 500 words in length) of a specific research question and/or a set of hypotheses that s/he would like to examine via an experimental approach. This outline (in PDF format, file name format: "LastName-FirstName-ResQues.pdf") should be e-mailed to ghaeubl@ualberta.ca with "GSERM-EMBS" as the subject line by 23:00 (St. Gallen time) on Friday prior course start.
As part of the introductions on the first morning of the course, students be will be asked to give 2-minute presentations on these research questions/hypotheses (and to say a few words about their areas of research interest more broadly).

The objectives behind this assignment are:
• to facilitate learning by ensuring that students have their own concrete research questions/hypotheses in mind as they engage with the material covered in the course
• to provide the instructor with input for tailoring the course content and/or class discussions to students' interests

Course content
The objective of this course is to provide students with an understanding of the essential principles and techniques for conducting scientific experiments on human behavior. It is tailored for individuals with an interest in doing research (using experimental methods) in areas such as psychology, judgment and decision making, behavioral economics, consumer behavior, organizational behavior, and human performance. The course covers a variety of topics, including the formulation of research hypotheses, the construction of experimental designs, the development of experimental tasks and stimuli, how to avoid confounds and other threats to validity, procedural aspects of administering experiments, the analysis of experimental data, and the reporting of results obtained from experiments. Classes are conducted in an interactive seminar format, with extensive discussion of concrete examples, challenges, and solutions.

Topics
The topics covered in the course include:
• Basic principles of experimental research
• Formulation of research question and hypothesis development
• Experimental paradigms
• Design and manipulation
• Measurement
• Factorial designs
• Implementation of experiments
• Data analysis and reporting of results
• Advanced methods and complex experimental designs
• Ethical issues

Literature

Recommended
There is no textbook for this course.

However, here are some recommended books on the design (and analysis) of experiments:

Abdi, Edelman, Valentin, and Dowling (2009), Experimental Design and Analysis for Psychology, Oxford University Press.

Field and Hole (2003), How to Design and Report Experiments, Sage.

Keppel and Wickens (2004), Design and Analysis: A Researcher's Handbook, Pearson.

Kirk (2013), Experimental Design: Procedures for the Behavioral Sciences, Sage.

Martin (2007), Doing Psychology Experiments, Wadsworth.

Oehlert (2010), A First Course in Design and Analysis of Experiments, available online at:
http://users.stat.umn.edu/~gary/book/fcdae.pdf.

In addition, the following papers are recommended as background readings for the course:

Cumming, Geoff (2014), "The New Statistics: Why and How," Psychological Science, 25, 1, 7-29.

Elrod, Häubl, and Tipps (2012), "Parsimonious Structural Equation Models for Repeated Measures Data, With Application to the Study of Consumer Preferences," Psychometrika, 77, 2, 358-387.

Goodman and Paolacci (2017), "Crowdsourcing Consumer Research," Journal of Consumer Research, 44, 1, 196-210.

McShane and Böckenholt (2017), "Single-Paper Meta-Analysis: Benefits for Study Summary, Theory Testing, and Replicability," Journal of Consumer Research, 43, 6, 1048-1063.

Meyvis and Van Osselaer (2018), "Increasing the Power of Your Study by Increasing the
Effect Size," Journal of Consumer Research, 44, 5, 1157-1173.

Morales, Amir, and Lee (2017), "Keeping It Real in Experimental Research-Understanding When, Where, and How to Enhance Realism and Measure Consumer Behavior," Journal of Consumer Research, 44, 2, 465-476.

Oppenheimer, Meyvis, and Davidenko (2009), "Instructional Manipulation Checks: Detecting Satisficing to Increase Statistical Power," Journal of Experimental Social Psychology, 45, 867-872.

Pieters (2017), "Meaningful Mediation Analysis: Plausible Causal Inference and Informative Communication," Journal of Consumer Research, 44, 3, 692-716.

Simmons, Nelson, and Simonsohn (2011), "False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant," Psychological Science, 22, 11, 1359-1366.

Simonsohn, Nelson, and Simmons (2014), "P-Curve: A Key to the File-Drawer," Journal of Experimental Psychology: General, 143, 2, 534-547.

Spiller, Fitzsimons, Lynch, and McClelland (2013), "Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression," Journal of Marketing Research, 50, 277-288.

Zhao, Lynch, and Chen (2010), "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, 37, 197-206.

Examination part
Students are to complete a (2-hour) written exam in the afternoon of the last day of class. In the exam, students are given a description of a research question, along with specific hypotheses. They are to produce a proposal for an experiment, or a series of experiments, for testing these hypotheses. The exam is "open book" - that is, students are free to use any appropriate local resources they wish in developing their proposal. (Here, "local" means that students may not access the Internet or other communication networks.)

Regular attendance and active participation in class discussion are expected.

Common standards of academic integrity apply. Work submitted by students must be their own - submitting what someone else has created is not acceptable.

Grading
A student's overall grade is based on the following components:

- Initial Assignment and Presentation: 10%
- Class Participation: 20%
- Exam: 70%