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Measurement error when surveying issue positions: a MultiTrait MultiError approach

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  • Backström, Kim
  • Cernat, Alexandru
  • Sirén, Rasmus
  • Söderlund, Peter

Abstract

Voters’ issue preferences are key determinants of vote choice, making it essential to reduce measurement error in responses to issue questions in surveys. This study uses a MultiTrait MultiError approach to assess the data quality of issue questions by separating four sources of variation: trait, acquiescence, method, and random error. The questions generally achieved moderate data quality, with 76% on average representing valid variance. Random error made up the largest proportion of error (23%). Error due to method and acquiescence was small. We found that 5-point scales are generally better than 11-point scales, while answers by respondents with lower political sophistication achieved lower data quality. The findings indicate a need to focus on decreasing random error when studying issue positions.

Suggested Citation

  • Backström, Kim & Cernat, Alexandru & Sirén, Rasmus & Söderlund, Peter, 2026. "Measurement error when surveying issue positions: a MultiTrait MultiError approach," Political Science Research and Methods, Cambridge University Press, vol. 14(2), pages 472-489, April.
    • Handle: RePEc:cup:pscirm:v:14:y:2026:i:2:p:472-489_12
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