Literature DB >> 28130934

Response style analysis with threshold and multi-process IRT models: A review and tutorial.

Ulf Böckenholt1, Thorsten Meiser2.   

Abstract

Two different item response theory model frameworks have been proposed for the assessment and control of response styles in rating data. According to one framework, response styles can be assessed by analysing threshold parameters in Rasch models for ordinal data and in mixture-distribution extensions of such models. A different framework is provided by multi-process item response tree models, which can be used to disentangle response processes that are related to the substantive traits and response tendencies elicited by the response scale. In this tutorial, the two approaches are reviewed, illustrated with an empirical data set of the two-dimensional 'Personal Need for Structure' construct, and compared in terms of multiple criteria. Mplus is used as a software framework for (mixed) polytomous Rasch models and item response tree models as well as for demonstrating how parsimonious model variants can be specified to test assumptions on the structure of response styles and attitude strength. Although both frameworks are shown to account for response styles, they differ on the quantitative criteria of model selection, practical aspects of model estimation, and conceptual issues of representing response styles as continuous and multidimensional sources of individual differences in psychological assessment.
© 2017 The British Psychological Society.

Keywords:  MPLUS; attitudinal measurement; item-response tree models; response style; threshold item-response models

Mesh:

Year:  2017        PMID: 28130934     DOI: 10.1111/bmsp.12086

Source DB:  PubMed          Journal:  Br J Math Stat Psychol        ISSN: 0007-1102            Impact factor:   3.380


  12 in total

1.  Extreme Response Style: A Simulation Study Comparison of Three Multidimensional Item Response Models.

Authors:  Brian C Leventhal
Journal:  Appl Psychol Meas       Date:  2018-08-01

2.  Item Response Tree Models to Investigate Acquiescence and Extreme Response Styles in Likert-Type Rating Scales.

Authors:  Minjeong Park; Amery D Wu
Journal:  Educ Psychol Meas       Date:  2019-02-15       Impact factor: 2.821

3.  Using multidimensional item response theory to evaluate how response styles impact measurement.

Authors:  Daniel J Adams; Daniel M Bolt; Sien Deng; Stevens S Smith; Timothy B Baker
Journal:  Br J Math Stat Psychol       Date:  2019-03-28       Impact factor: 3.380

4.  Measuring Response Style Stability Across Constructs With Item Response Trees.

Authors:  Allison J Ames
Journal:  Educ Psychol Meas       Date:  2021-06-02       Impact factor: 2.821

5.  A Mixture IRTree Model for Extreme Response Style: Accounting for Response Process Uncertainty.

Authors:  Nana Kim; Daniel M Bolt
Journal:  Educ Psychol Meas       Date:  2020-04-27       Impact factor: 2.821

6.  Explaining Variability in Response Style Traits: A Covariate-Adjusted IRTree.

Authors:  Allison J Ames; Aaron J Myers
Journal:  Educ Psychol Meas       Date:  2020-11-04       Impact factor: 3.088

7.  A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data.

Authors:  Esther Ulitzsch; Steffi Pohl; Lale Khorramdel; Ulf Kroehne; Matthias von Davier
Journal:  Psychometrika       Date:  2021-12-02       Impact factor: 2.290

8.  The Relationship of Insufficient Effort Responding and Response Styles: An Online Experiment.

Authors:  Gene M Alarcon; Michael A Lee
Journal:  Front Psychol       Date:  2022-01-12

9.  Modeling Faking in the Multidimensional Forced-Choice Format: The Faking Mixture Model.

Authors:  Susanne Frick
Journal:  Psychometrika       Date:  2021-12-20       Impact factor: 2.290

10.  Validity of Three IRT Models for Measuring and Controlling Extreme and Midpoint Response Styles.

Authors:  Yingbin Zhang; Yehui Wang
Journal:  Front Psychol       Date:  2020-02-21
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