Advances in Experimental Political Science

James N. Druckman · Donald P. Green

Apr 2021 · Cambridge University Press

About this ebook

Experimental political science has changed. In two short decades, it evolved from an emergent method to an accepted method to a primary method. The challenge now is to ensure that experimentalists design sound studies and implement them in ways that illuminate cause and effect. Ethical boundaries must also be respected, results interpreted in a transparent manner, and data and research materials must be shared to ensure others can build on what has been learned. This book explores the application of new designs; the introduction of novel data sources, measurement approaches, and statistical methods; the use of experiments in more substantive domains; and discipline-wide discussions about the robustness, generalizability, and ethics of experiments in political science. By exploring these novel opportunities while also highlighting the concomitant challenges, this volume enables scholars and practitioners to conduct high-quality experiments that will make key contributions to knowledge.

About the author

James N. Druckman is the Payson S. Wild Professor of Political Science at Northwestern University. He was elected to the American Academy of Arts and Sciences and, with Donald Green, helped found the Experimental Research section of the American Political Science Association. He also is currently the co-Principal Investigator for Time-sharing Experiments in the Social Sciences, and co-authored the book Who Governs? Presidents, Public Opinion, and Manipulation.

Donald P. Green is the J.W. Burgess Professor of Political Science at Columbia University. He was elected to the American Academy of Arts and Sciences and, with James Druckman, helped found the Experimental Research section of the American Political Science Association. He also co-founded the scholarly consortium of experimental researchers, Evidence in Governance and Politics, and co-authored the textbook Field Experiments: Design, Analysis, and Interpretation.