Experimental Methods   

Professors Jerit and Barabas' course provided us with a great overview of the field. They also gave us really helpful feedback and are super approachable. — participant from China

Experimental research has come to occupy a central place in the social and behavioral sciences as well as the development and study of public policy as academic scholars and practitioners in non-governmental organizations, consulting, and the civil service alike have become more concerned about making valid causal inferences. The purpose of this course is to learn about the use of experiments in the social sciences and related fields, develop an understanding of the experimental method (e.g., its strengths and weaknesses relative to other methodologies), and gain experience in designing experimental studies, such as lab-based randomized controlled trial (RCT), survey experiments, and field experiments.

Participants with a basic background in game theory should consider combining Experimental Methods with Game Theory II. Participants with an interest in the design and analysis of public policy might want to complement the course with advanced Quantitative Public Policy Analysis II during the second week of the Methods School.


Dates

This one-week, 20-hour course runs Monday-Friday, 9:00 am-1:00 pm, June 19-23, 2017.


Instructors

Jennifer Jerit (picture), Stony Brook University
Jason Barabas (picture), Stony Brook University


Detailed Description

In this course, participants will gain a broad understanding of the issues involved in the design and analysis of experiments. The course is organized into four sections corresponding to some of the practical issues that arise in experimental research.

The first section of the course covers the foundations of the experimental method and the theory of causal inference. We discuss the general principles that are common to all experimental practice (e.g., standardization, control, and random assignment) and the tradeoffs between internal and external validity.

The second part of the course discusses how to translate one's theory or conceptual model into an experimental design. In this portion of the class we discuss construct validity, questionnaire design, and different types of experimental designs. We will also cover such related topics as (1) the location – lab, field, or survey – of one's study, (2) different types of subject populations, and (3) methods of compensation.

The third section of the course is devoted to the analysis of experimental data and related topics such as mediation, heterogeneous treatment effects, statistical power, and exact tests. We also discuss some of the challenges that arise in the execution of experimental research, such as inattentive subjects, non-compliance, and variation in treatment effects across different modes or styles of experiments (e.g., lab versus field).

Finally, we will discuss some of the ethical considerations involved in experimental research. We consider the role of informed consent, the debate over deception, the risks and benefits from experimentation for subjects and third parties in the lab and field, and the practical issues in dealing with human subject committees/Institutional Review Boards (IRB).


Prerequisites

There are no formal prerequisites. However, familiarity with some basic statistical concepts would be beneficial.


Requirements

Participants are expected to bring a WiFi-enabled laptop computer. Access to data, temporary licenses for the course software, and installation support will be provided by the Methods School.


Core Readings

Druckman, James N., Donald P. Green, James H. Kuklinski, and Arthur Lupia. 2011. Cambridge Handbook of Experimental Political Science. New York, NY: Cambridge University Press.


Suggested Readings

Morton, Rebecca B., and Kenneth C. Williams. 2010. From Nature to the Lab. Experimental Political Science and the Study of Causality. New York, NY: Cambridge University Press.

Gerber, Alan S., and Donald P. Green. 2012. Field Experiments: Design, Analysis, and Interpretation. New York, NY: W.W. Norton & Company.

Mutz, Diana C. 2011. Population Based Survey Experiments. Princeton, NJ: Princeton University Press.


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