A Simulation Study on Methods of Correcting for the Effects of Extreme Response Style

Eunike Wetzel, Jan Rasmus Boehnke, Norman Rose

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    19 Citations (Scopus)


    The impact of response styles such as extreme response style (ERS) on trait estimation has long been a matter of concern to researchers and practitioners. This simulation study investigated three methods that have been proposed for the correction of trait estimates for ERS effects: (a) mixed Rasch models, (b) multidimensional item response models, and (c) regression residuals. The methods were compared with respect to their ability of recovering the true latent trait levels. Data were generated according to a unidimensional model with only one trait, a mixed Rasch model with two populations of ERS and non-ERS, and a two-dimensional model incorporating a trait and an ERS dimension. The data were analyzed using the same models as well as linear regression where the trait estimate is regressed on an ERS score and the resulting residual is considered the corrected trait estimate. Over all conditions, the two-dimensional model achieved the best trait recovery, though the difference to the unidimensional model was rather small. Mixed Rasch models were in general inferior to the other correction methods. When the trait and ERS showed no to weak correlations, ERS appeared to have a minor impact on trait estimation.
    Original languageEnglish
    Pages (from-to)304-324
    Number of pages21
    JournalEducational and Psychological Measurement
    Issue number2
    Early online date29 Jun 2015
    Publication statusPublished - 1 Apr 2016


    • response styles
    • extreme response style
    • mixed Rasch models
    • multidimensional item response models
    • regression residuals


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