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Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated... Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis , an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants. © The Author 2013. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oup.com « Previous | Next Article » Table of Contents This Article Political Analysis (Winter 2014) 22 (1): 1-30. doi: 10.1093/pan/mpt024 First published online: December 19, 2013 » Abstract Free Full Text (HTML) Free Full Text (PDF) Free Supplementary Data All Versions of this Article: mpt024v1 22/1/1 most recent Classifications Article Services Article metrics Alert me when cited Alert me if corrected Find similar articles Similar articles in Web of Science Add to my archive Download citation Request Permissions Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Hainmueller, J. Articles by Yamamoto, T. Search for related content Related Content Load related web page information Share Email this article CiteULike Delicious Facebook Google+ Mendeley Twitter What's this? Search this journal: Advanced » Current Issue Summer 2015 23 (3) Alert me to new issues The Journal About this journal Impact Factor Articles Special Issues Virtual Issues Editors Choice Articles Political Analysis on OUPblog Follow @polanalysis !function(d,s,id){var js,fjs=d.getElementsByTagName(s)(0),p=/^http:/.test(d.location)?'http':'https';if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src=p+'://platform.twitter.com/widgets.js';fjs.parentNode.insertBefore(js,fjs);}}(document, 'script', 'twitter-wjs'); Political Analysis on Facebook Political Analysis Dataverse Rights & Permissions Dispatch date of the next issue We are mobile – find out more Journals Career Network Impact Factor: 4.655 5-Yr impact factor: 4.659 Published on behalf of The Society for Political Methodology and the Political Methodology Section of the American Political Science Association Editor-in-Chief R. Michael Alvarez and Jonathan N. Katz View full editorial board For Authors Instructions to authors Self-archiving Policy Online submission Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed Corporate Services Advertising sales Reprints Supplements var taxonomies = ("SOC02270"); Most Most Read Understanding Interaction Models: Improving Empirical Analyses Estimating Voter Registration Deadline Effects with Web Search Data Measure for Measure: An Experimental Test of Online Political Media Exposure Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data » View all Most Read articles Most Cited Understanding Interaction Models: Improving Empirical Analyses Logistic Regression in Rare Events Data Back to the Future: Modeling Time Dependence in Binary Data Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999 » View all Most Cited articles Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department. 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Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

Political Analysis , Volume 22 (1) – Jan 1, 2014

Abstract

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis , an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants. © The Author 2013. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oup.com « Previous | Next Article » Table of Contents This Article Political Analysis (Winter 2014) 22 (1): 1-30. doi: 10.1093/pan/mpt024 First published online: December 19, 2013 » Abstract Free Full Text (HTML) Free Full Text (PDF) Free Supplementary Data All Versions of this Article: mpt024v1 22/1/1 most recent Classifications Article Services Article metrics Alert me when cited Alert me if corrected Find similar articles Similar articles in Web of Science Add to my archive Download citation Request Permissions Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Hainmueller, J. Articles by Yamamoto, T. Search for related content Related Content Load related web page information Share Email this article CiteULike Delicious Facebook Google+ Mendeley Twitter What's this? Search this journal: Advanced » Current Issue Summer 2015 23 (3) Alert me to new issues The Journal About this journal Impact Factor Articles Special Issues Virtual Issues Editors Choice Articles Political Analysis on OUPblog Follow @polanalysis !function(d,s,id){var js,fjs=d.getElementsByTagName(s)(0),p=/^http:/.test(d.location)?'http':'https';if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src=p+'://platform.twitter.com/widgets.js';fjs.parentNode.insertBefore(js,fjs);}}(document, 'script', 'twitter-wjs'); Political Analysis on Facebook Political Analysis Dataverse Rights & Permissions Dispatch date of the next issue We are mobile – find out more Journals Career Network Impact Factor: 4.655 5-Yr impact factor: 4.659 Published on behalf of The Society for Political Methodology and the Political Methodology Section of the American Political Science Association Editor-in-Chief R. Michael Alvarez and Jonathan N. Katz View full editorial board For Authors Instructions to authors Self-archiving Policy Online submission Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed Corporate Services Advertising sales Reprints Supplements var taxonomies = ("SOC02270"); Most Most Read Understanding Interaction Models: Improving Empirical Analyses Estimating Voter Registration Deadline Effects with Web Search Data Measure for Measure: An Experimental Test of Online Political Media Exposure Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data » View all Most Read articles Most Cited Understanding Interaction Models: Improving Empirical Analyses Logistic Regression in Rare Events Data Back to the Future: Modeling Time Dependence in Binary Data Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999 » View all Most Cited articles Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department. Online ISSN 1476-4989 - Print ISSN 1047-1987 Copyright © 2015 Society for Political Methodology Oxford Journals Oxford University Press Site Map Privacy Policy Cookie Policy Legal Notices Frequently Asked Questions Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan Academic & Professional books Children's & Schools Books Dictionaries & Reference Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks International Education Unit Law Medicine Music Online Products & Publishing Oxford Bibliographies Online Oxford Dictionaries Online Oxford English Dictionary Oxford Language Dictionaries Online Oxford Scholarship Online Reference Rights and Permissions Resources for Retailers & Wholesalers Resources for the Healthcare Industry Very Short Introductions World's Classics function fnc_onDomLoaded() { var query_context = getQueryContext(); PF_initOIUnderbar(query_context,":QS:default","","JRN"); PF_insertOIUnderbar(0); }; if (window.addEventListener) { window.addEventListener('load', fnc_onDomLoaded, false); } else if (window.attachEvent) { window.attachEvent('onload', fnc_onDomLoaded); } var gaJsHost = (("https:" == document.location.protocol) ? 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References (74)

Publisher
Oxford University Press
Copyright
Copyright © 2015 Society for Political Methodology
ISSN
1047-1987
eISSN
1476-4989
DOI
10.1093/pan/mpt024
Publisher site
See Article on Publisher Site

Abstract

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis , an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants. © The Author 2013. Published by Oxford University Press on behalf of the Society for Political Methodology. All rights reserved. For Permissions, please email: journals.permissions@oup.com « Previous | Next Article » Table of Contents This Article Political Analysis (Winter 2014) 22 (1): 1-30. doi: 10.1093/pan/mpt024 First published online: December 19, 2013 » Abstract Free Full Text (HTML) Free Full Text (PDF) Free Supplementary Data All Versions of this Article: mpt024v1 22/1/1 most recent Classifications Article Services Article metrics Alert me when cited Alert me if corrected Find similar articles Similar articles in Web of Science Add to my archive Download citation Request Permissions Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Citing articles via Web of Science Citing articles via Google Scholar Google Scholar Articles by Hainmueller, J. Articles by Yamamoto, T. Search for related content Related Content Load related web page information Share Email this article CiteULike Delicious Facebook Google+ Mendeley Twitter What's this? Search this journal: Advanced » Current Issue Summer 2015 23 (3) Alert me to new issues The Journal About this journal Impact Factor Articles Special Issues Virtual Issues Editors Choice Articles Political Analysis on OUPblog Follow @polanalysis !function(d,s,id){var js,fjs=d.getElementsByTagName(s)(0),p=/^http:/.test(d.location)?'http':'https';if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src=p+'://platform.twitter.com/widgets.js';fjs.parentNode.insertBefore(js,fjs);}}(document, 'script', 'twitter-wjs'); Political Analysis on Facebook Political Analysis Dataverse Rights & Permissions Dispatch date of the next issue We are mobile – find out more Journals Career Network Impact Factor: 4.655 5-Yr impact factor: 4.659 Published on behalf of The Society for Political Methodology and the Political Methodology Section of the American Political Science Association Editor-in-Chief R. Michael Alvarez and Jonathan N. Katz View full editorial board For Authors Instructions to authors Self-archiving Policy Online submission Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed Corporate Services Advertising sales Reprints Supplements var taxonomies = ("SOC02270"); Most Most Read Understanding Interaction Models: Improving Empirical Analyses Estimating Voter Registration Deadline Effects with Web Search Data Measure for Measure: An Experimental Test of Online Political Media Exposure Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data » View all Most Read articles Most Cited Understanding Interaction Models: Improving Empirical Analyses Logistic Regression in Rare Events Data Back to the Future: Modeling Time Dependence in Binary Data Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999 » View all Most Cited articles Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department. Online ISSN 1476-4989 - Print ISSN 1047-1987 Copyright © 2015 Society for Political Methodology Oxford Journals Oxford University Press Site Map Privacy Policy Cookie Policy Legal Notices Frequently Asked Questions Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan Academic & Professional books Children's & Schools Books Dictionaries & Reference Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks International Education Unit Law Medicine Music Online Products & Publishing Oxford Bibliographies Online Oxford Dictionaries Online Oxford English Dictionary Oxford Language Dictionaries Online Oxford Scholarship Online Reference Rights and Permissions Resources for Retailers & Wholesalers Resources for the Healthcare Industry Very Short Introductions World's Classics function fnc_onDomLoaded() { var query_context = getQueryContext(); PF_initOIUnderbar(query_context,":QS:default","","JRN"); PF_insertOIUnderbar(0); }; if (window.addEventListener) { window.addEventListener('load', fnc_onDomLoaded, false); } else if (window.attachEvent) { window.attachEvent('onload', fnc_onDomLoaded); } var gaJsHost = (("https:" == document.location.protocol) ? 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Journal

Political AnalysisOxford University Press

Published: Jan 1, 2014

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