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Field Experiments: Design, Analysis, and Interpretation, by Alan S. Gerber, Donald P. Green
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A brief, authoritative introduction to field experimentation in the social sciences.
Written by two leading experts on experimental methods, this concise text covers the major aspects of experiment design, analysis, and interpretation in clear language. Students learn how to design randomized experiments, analyze the data, and interpret the findings. Beyond the authoritative coverage of the basic methodology, the authors include numerous features to help students achieve a deeper understanding of field experimentation, including rich examples from the social science literature, problem sets and discussions, data sets, and further readings.- Sales Rank: #167285 in Books
- Published on: 2012-05-29
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.00" w x 6.20" l, 1.55 pounds
- Binding: Paperback
- 480 pages
About the Author
Alan S. Gerber is Professor of Political Science and Director of the Center for the Study of American Politics at Yale University where he teaches courses on experimental methods, statistics, and American politics. His experimental research has appeared in numerous academic journals including the leading journals in political science.
Donald P. Green is Professor of Political Science at Columbia University, and the former director of Yale University’s Institution for Social and Policy Research. He is the author of numerous articles and several scholarly books on voter turnout, party identification, and experimental methods, including Get Out the Vote: How to Increase Voter Turnout (with Alan S. Gerber).
Most helpful customer reviews
7 of 7 people found the following review helpful.
Authoritative text on experimental methods for the social sciences. Well written and accessible
By kyle peyton
This is a great book. It's well written, concise and offers a rigorous first course in experimental methods that is essentially free from disciplinary jargon. It also fills an important void in being really the only text on the design and analysis of experiments written for social scientists. There are plenty of examples, exercises and datasets here so the book also serves as a great text for self study. The book has the added advantage of conveying a nuanced understanding of the implementation challenges that result from experiments on humans that many statistics texts (typically written with crop yields or bacteria in mind) fall short on.
1 of 1 people found the following review helpful.
Excellent resource on intent to treat and compliance in field experiments
By Ayman Farahat
This is a very useful book on running randomized experiments. The book has a very good survey of randomized inference but where the book really excels is intent to treat and compliance. In a world where compliance is an real issue, this book provides very practical solutions. The R code makes it very easy to follow the econometrics.
0 of 0 people found the following review helpful.
This is a really nice, accessible treatment of the Rubin causal model with ...
By D. A. Hughes
This is a really nice, accessible treatment of the Rubin causal model with specific applications to Political Science and Development. More than that though, it does a *very* good job of balancing accessibility/readability/rigor.
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