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Extreme response style (ERS) can bias questionnaire results. This study compares two item response theory (IRT) models, finding they yield different conclusions about group differences when ERS varies across cultures.

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Area of Science:

  • Psychometrics
  • Cross-cultural Psychology
  • Statistical Modeling

Background:

  • Extreme response style (ERS) compromises the validity of Likert-type questionnaire data.
  • Item response theory (IRT) models are used to address ERS, but comparisons are limited, especially in cross-cultural research.
  • Cultural differences can exacerbate ERS, making cross-cultural comparisons particularly susceptible to bias.

Purpose of the Study:

  • To compare two common IRT models: the multidimensional nominal response model (MNRM) and the IRTree model.
  • To investigate the conceptual differences in how these models handle ERS.
  • To evaluate the impact of these model differences on cross-cultural comparisons of substantive traits.

Main Methods:

  • Conceptual analysis of the MNRM and IRTree models regarding ERS.
  • A simulation study was conducted to assess model performance in a multigroup context.
  • An empirical example was used to illustrate the practical implications.

Main Results:

  • The MNRM and IRTree models conceptualize ERS differently, leading to distinct category probabilities.
  • In simulations, when groups differed in average ERS, the models produced substantially different conclusions regarding trait differences.
  • The choice of IRT model significantly impacts the interpretation of cross-cultural differences in substantive traits.

Conclusions:

  • The conceptualization of ERS within IRT models critically affects cross-cultural comparative analyses.
  • Researchers must carefully consider the chosen IRT model's assumptions and implications for ERS when conducting multigroup studies.
  • Further research is needed to refine ERS modeling and its application in cross-cultural psychometric research.