Workshop or Training
Advanced Workshop: Designing, Conducting, and Analyzing Field Experiments
This is a three-day short course taught by Columbia University Professor of Political Science, and J-PAL affiliate, Donald P. Green, hosted by J-PAL. In this short course you will:
- Hone your expertise on experiments as a tool for social science research and program evaluation.
- Learn about recent advances on how field experiments are designed, executed and analyzed illustrated with in-depth examples and research papers
- Explore and develop your own research ideas through discussion with peers and specialists.
Who should attend
We welcome participants who are currently, or planning to be involved in conducting impact evaluations, and want a deeper theoretical and practical understanding of how to design, monitor, and analyze data from field experiments. Familiarity with basic mathematical notation, statistical concepts, and statistical programming is highly recommended. We hope to create a rich interdisciplinary setting in which participants from different academic disciplines and those with non-academic technical backgrounds can discuss their research ideas.
What topics does this course cover?
We start the course by introducing randomized experiments and motivating their use in the social sciences. We then focus on how to perform statistical inference under randomization, discussing both regression models and “randomization inference”. We consider a variety of design choices or departures from “ideal” experimental conditions that have implications for the analysis of experimental data. In particular, we consider the complications that arise when (1) treatment and control conditions differ in systematic ways other than the intended treatment, (2) treatments are not administered according to the randomly assigned plan, (3) subjects not assigned to treatment are indirectly affected by the treatments, and (4) outcome measures are not obtained for all subjects. We conclude by discussing the practical issues that arise when conducting experiments in field settings. The course will consist of readings from Field Experiments: Design, Analysis, and Interpretation by Alan Gerber and Don Green, a series of lectures by Don Green, facilitated exercises that use the statistical programming languages R and Stata, and classroom discussions.
Donald P. Green is the John William Burgess Professor at Columbia University, having moved there in 2011 after 22 years at Yale University. The author of four books and more than one hundred essays, Green's research interests span a wide array of topics: voting behavior, partisanship, campaign finance, hate crime, and research methods. Much of his current work uses field experimentation to study the ways in which political campaigns mobilize and persuade voters. He was elected to the American Academy of Arts and Sciences in 2003 and was awarded the Heinz I. Eulau Award for best article published in the American Political Science Review during 2009. In 2010, he helped found the Experimental Research section of the American Political Science Association and served as its first president. He is also a J-PAL affiliate. Green's current research projects examine the effects of mass media on social attitudes in Uganda and vote buying in India.
|Dates:||August 1-3 2017|
|Location:||Massachusetts Institute of Technology
|Contacts:||Tom Bangura; [email protected]
Janani Akhilandeswari; [email protected]
Course fee: $1,000. This fee includes tuition, course materials, lunch, and light refreshments. Travel and accommodation are not included.