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Strengthening the Experimenter’s Toolbox

Statistical Estimation of Internal Validity

Bibliographic Data

ID6231023
AuthorsLuke Keele (0000-0002-3859-2713, Pennsylvania State University), Corrine M Mcconnaughy (0000-0001-5893-869X, The Ohio State University), Corrine Mcconnaughy, Ismail K White (The Ohio State University), Ismail White
Year2012
Volume56
Issue2
Pages484-499
Publication date2012-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Political Science (JOURNAL)
Journal identifiersISSN: 0092-5853 • E-ISSN: 1540-5907
PublisherWiley (PUBLISHER • GB)
DOI10.1111/j.1540-5907.2011.00576.x
OpenAlexW2143335126
LanguageEN
Citations received34
References cited20

Experiments have become an increasingly common tool for political science researchers over the last decade, particularly laboratory experiments performed on small convenience samples. We argue that the standard normal theory statistical paradigm used in political science fails to meet the needs of these experimenters and outline an alternative approach to statistical inference based on randomization of the treatment. The randomization inference approach not only provides direct estimation of the experimenter’s quantity of interest—the certainty of the causal inference about the observed units—but also helps to deal with other challenges of small samples. We offer an introduction to the logic of randomization inference, a brief overview of its technical details, and guidance for political science experimenters about making analytic choices within the randomization inference framework. Finally, we reanalyze data from two political science experiments using randomization tests to illustrate the inferential differences that choosing a randomization inference approach can make

Bayesian inference · Bayesian probability · Causal inference · Data science · Econometrics · Fiducial inference · Frequentist inference · Inference · Machine learning · Randomization · Randomized controlled trial · Statistical inference · Statistical theory · Statistics · Toolbox · Advanced Causal Inference Techniques · Artificial Intelligence · Computer Science · Electoral Systems and Political Participation · Mathematics · Qualitative Comparative Analysis Research

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Unique citing works34
Citations per year2,62
Citation span2013 - 2026 (14)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 34

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