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Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data.

Authors
  • Büschken, Joachim1
  • Böckenholt, Ulf2
  • Otter, Thomas3
  • Stengel, Daniel4
  • 1 Catholic University of Eichstätt-Ingolstadt, Eichstätt, Germany. , (Germany)
  • 2 Kellogg School of Management, Northwestern University, Evanston, USA. [email protected]
  • 3 Goethe University, Frankfurt, Germany. , (Germany)
  • 4 GfK, Nuremberg, Germany. , (Germany)
Type
Published Article
Journal
Psychometrika
Publication Date
Jun 01, 2022
Volume
87
Issue
2
Pages
620–665
Identifiers
DOI: 10.1007/s11336-021-09814-w
PMID: 34698978
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Ideally, survey respondents read and understand survey instructions, questions, and response scales, and provide answers that carefully reflect their beliefs, attitudes, or knowledge. However, respondents may also arrive at their responses using cues or heuristics that facilitate the production of a response, but diminish the targeted information content. We use eye-tracking data as covariates in a Bayesian switching-mixture model to identify different response behaviors at the item-respondent level. The model distinguishes response behaviors that are predominantly influenced either positively or negatively by the previous response, and responses that reflect respondents' preexisting knowledge and experiences of interest. We find that controlling for multiple types of adaptive response behaviors allows for a more informative analysis of survey data and respondents. © 2021. The Psychometric Society.

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