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Don’t Know What You Got: A Bayesian Hierarchical Model of Neuroticism and Nonresponse*

Published online by Cambridge University Press:  07 December 2016

Jonathan D. Klingler ,
Gary E. Hollibaugh Jr.  and
Adam J. Ramey
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Abstract

Individuals who are more sensitive to negative outcomes from error are more likely to provide nonresponses in surveys. We argue Neurotics’ sensitivity to negative outcomes leads them to avoid gathering costly information and forming/reporting opinions about stimuli. Using data from the 2014 Cooperative Congressional Election Study, we show Neuroticism is strongly and positively associated with NA/DK responses when placing politicians on a seven-point ideological scale. We then introduce to political science a Bayesian hierarchical model that allows nonresponse to be generated by both a lack of information as well as disincentives for response. Using this model, we show that the NA/DK responses in these data are due to inhibited information collection and indecision from error avoidance by Neurotics.

Type
Original Articles
Information
Political Science Research and Methods , Volume 6 , Issue 3 , July 2018 , pp. 549 - 569
Copyright
© The European Political Science Association 2016 

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Footnotes

*

Jonathan D. Klingler is a Postdoctoral Scholar in the Department of Political Science, Vanderbilt University, PMB 505, 230 Appleton Place, Nashville, TN 37203 (jonathan.d.klingler@vanderbilt.edu). Gary E. Hollibaugh, Jr. is an Assistant Professor in the Department of Political Science, University of Notre Dame, Notre Dame, IN 46556 (gholliba@nd.edu). Adam J. Ramey is an Assistant Professor in the Department of Politics, New York University Abu Dhabi, PO Box 129188, Abu Dhabi (adam.ramey@nyu.edu). Author order was determined by a spirited game of Diplomacy. All authors contributed equally to the paper. The authors thank Megan Remmel for feedback and comments. Support through ANR–Labex IAST and the University of Notre Dame Center for Research Computing is gratefully acknowledged. To view supplementary material for this article, please visit https://doi.org/10.1017/psrm.2016.50

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Klingler et al Dataset

Dataset

http://dx.doi.org/10.7910/DVN/RVV3YW
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Klingler supplementary material

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