Measurement error when surveying issue positions

A MultiTrait MultiError approach

Dados Bibliográficos

ID6342199
AutoresKim Backström (0000-0002-1941-5922), Alexandru Cernat (0000-0001-6007-7825), Alex Cernat (0000-0003-2176-1215), Rasmus Sirén (0000-0001-8005-2449), Peter Söderlund (0000-0002-5855-639X)
Ano2025
Páginas1-18
Data de publicação2025-05-02
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoPolitical Science Research and Methods (JOURNAL)
Identificadores do periódicoISSN: 2049-8470 • E-ISSN: 2049-8489
EditoraCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/psrm.2025.31
OpenAlexW4410039996
IdiomaEN
Referências citadas46

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

Econometrics · Economics · Statistics · Computer Science · Mathematics · Psychometric Methodologies and Testing · Statistical Methods and Bayesian Inference · Statistical Methods and Inference