Wording Effects in Assessment: Missing the Trees for the Forest

Fernando P. Ponce*, David Torres Irribarra, Alvaro Vergés, Victor B. Arias

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


This article examines wording effects when positive and negative worded items are included in psychological assessment. Wordings effects have been analyzed in the literature using statistical approaches based on population homogeneity assumptions (i.e. CFA, SEM), commonly adopting the bifactor model to separate trait variance and wording effects. This article presents an alternative approach by explicitly modeling population heterogeneity through a latent profile model, based on the idea that a subset of individuals exhibits wording effects. This kind of mixture model allows simultaneously to classify respondents, substantively characterize the differences in their response profiles, and report respondents' results in a comparable manner. Using the Rosenberg’s self-esteem scale data from the LISS Panel (N = 6,762) in three studies, we identify a subgroup of participants who respond differentially according to item-wording and examine the impact of its responses in the estimation of the RSES measurement model, in terms of global and individual fit, under one-factor and bifactor models. The results of these analyses support the interpretation of wording effects in terms of a theoretically-proposed differential pattern of response to positively and negatively worded items, introducing a valuable tool for examining the artifactual or substantive interpretations of such wording effects.

Original languageEnglish
Pages (from-to)718-734
Number of pages17
JournalMultivariate Behavioral Research
Issue number5
StatePublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.


  • confirmatory factor analysis
  • iteratively reweighted least squares
  • latent profile analysis
  • Rosenberg’s self-esteem scale
  • Wording effects


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