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Conjoint Survey Experiments

Bibliographic Data

ID23324304
AuthorsKirk Bansak (0000-0003-0229-9694), Jens Hainmueller (0000-0001-8214-9041), D J Hopkins (0000-0002-9085-6050), T Yamamoto (0000-0002-8079-7675)
Year2021
Pages19-41
Publication date2021-04-01
Peer ReviewedYes
Open AccessYes
TypeCHAPTER
VenueAdvances in Experimental Political Science (SOURCE_BOOK)
PublisherCambridge University Press (PUBLISHER • US)
DOI10.1017/9781108777919.004
OpenAlexW3133512891
ISBN9781108777919
LanguageEN
Citations received136
References cited10

Conjoint survey experiments have become a popular method for analyzing multidimensional preferences in political science. If properly implemented, conjoint experiments can obtain reliable measures of multidimensional preferences and estimate causal effects of multiple attributes on hypothetical choices or evaluations. This chapter provides an accessible overview of the methodology for designing, implementing, and analyzing conjoint survey experiments. Specically, we begin by detailing a new substantive example: how do candidate attributes affect the support of American respondents for candidates running against President Trump in 2020? We then discuss the theoretical underpinnings and key advantages of conjoint designs. We next provide guidelines for practitioners in designing and analyzing conjoint survey experiments. We conclude by discussing further design considerations, common conjoint applications, common criticisms, and possible future directions.

Conjoint analysis · Data science · Key (lock) · Management science · Operations research · Preference · Statistics · Artificial Intelligence · Computer Science · Decision-Making and Behavioral Economics · Economic and Environmental Valuation · Engineering · Mathematics

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Unique citing works136
Citations per year27,2
Citation span2021 - 2026 (6)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 123

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