Literature DB >> 29795817

Item Response Theory Models for Wording Effects in Mixed-Format Scales.

Wen-Chung Wang1, Hui-Fang Chen1,2, Kuan-Yu Jin1.   

Abstract

Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to test the assumption of reverse coding and evaluate the magnitude of the wording effect. The parameters of the bi-factor IRT models can be estimated with existing computer programs. Two empirical examples from the Program for International Student Assessment and the Trends in International Mathematics and Science Study were given to demonstrate the advantages of the bi-factor approach over traditional ones. It was found that the wording effect in these two data sets was substantial and that ignoring the wording effect resulted in overestimated test reliability and biased person measures.

Entities:  

Keywords:  Bayesian methods; bi-factor models; item response theory; wording effects

Year:  2014        PMID: 29795817      PMCID: PMC5965508          DOI: 10.1177/0013164414528209

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


  8 in total

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