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Comparing and Combining List and Endorsement Experiments

Evidence from Afghanistan

Bibliographic Data

ID6232025
AuthorsGraham Blair (0000-0001-9164-2102, Princeton University), Graeme Blair, Katsushi Imai (0000-0002-2748-1022, Princeton University), Kosuke Imai, James Lyall (0000-0001-9117-7503, Yale University), Jason Lyall
Year2014
Volume58
Issue4
Pages1043-1063
Publication date2014-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Political Science (JOURNAL)
Journal identifiersISSN: 0092-5853 • E-ISSN: 1540-5907
PublisherWiley (PUBLISHER • GB)
DOI10.1111/ajps.12086
OpenAlexW2097414408
LanguageEN
Citations received91
References cited22

List and endorsement experiments are becoming increasingly popular among social scientists as indirect survey techniques for sensitive questions. When studying issues such as racial prejudice and support for militant groups, these survey methodologies may improve the validity of measurements by reducing nonresponse and social desirability biases. We develop a statistical test and multivariate regression models for comparing and combining the results from list and endorsement experiments. We demonstrate that when carefully designed and analyzed, the two survey experiments can produce substantively similar empirical findings. Such agreement is shown to be possible even when these experiments are applied to one of the most challenging research environments: contemporary Afghanistan. We find that both experiments uncover similar patterns of support for the International Security Assistance Force (ISAF) among Pashtun respondents. Our findings suggest that multiple measurement strategies can enhance the credibility of empirical conclusions. Open‐source software is available for implementing the proposed methods

Credibility · Data science · Econometrics · Economics · Empirical research · External validity · Machine learning · Militant · Multivariate statistics · Political science · Politics · Prejudice (legal term · Randomized experiment · Statistics · Survey data collection · Test (biology · Applied Psychology · Computer Science · Law · Mathematics · Psychology · Social Psychology · Survey Sampling and Estimation Techniques

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