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IRTree models with ordinal and multidimensional decision nodes for response styles and trait-based rating responses


Meiser, Thorsten; Plieninger, Hansjörg; Henninger, Mirka (2019). IRTree models with ordinal and multidimensional decision nodes for response styles and trait-based rating responses. British Journal of Mathematical and Statistical Psychology, 72(3):501-516.

Abstract

IRTree models decompose observed rating responses into sequences of theory-based decision nodes, and they provide a flexible framework for analysing trait-related judgements and response styles. However, most previous applications of IRTree models have been limited to binary decision nodes that reflect qualitatively distinct and unidimensional judgement processes. The present research extends the family of IRTree models for the analysis of response styles to ordinal judgement processes for polytomous decisions and to multidimensional parametrizations of decision nodes. The integration of ordinal judgement processes overcomes the limitation to binary nodes, and it allows researchers to test whether decisions reflect qualitatively distinct response processes or gradual steps on a joint latent continuum. The extension to multidimensional node models enables researchers to specify multiple judgement processes that simultaneously affect the decision between competing response options. Empirical applications highlight the roles of extreme and midpoint response style in rating judgements and show that judgement processes are moderated by different response formats. Model applications with multidimensional decision nodes reveal that decisions among rating categories are jointly informed by trait-related processes and response styles.

Abstract

IRTree models decompose observed rating responses into sequences of theory-based decision nodes, and they provide a flexible framework for analysing trait-related judgements and response styles. However, most previous applications of IRTree models have been limited to binary decision nodes that reflect qualitatively distinct and unidimensional judgement processes. The present research extends the family of IRTree models for the analysis of response styles to ordinal judgement processes for polytomous decisions and to multidimensional parametrizations of decision nodes. The integration of ordinal judgement processes overcomes the limitation to binary nodes, and it allows researchers to test whether decisions reflect qualitatively distinct response processes or gradual steps on a joint latent continuum. The extension to multidimensional node models enables researchers to specify multiple judgement processes that simultaneously affect the decision between competing response options. Empirical applications highlight the roles of extreme and midpoint response style in rating judgements and show that judgement processes are moderated by different response formats. Model applications with multidimensional decision nodes reveal that decisions among rating categories are jointly informed by trait-related processes and response styles.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Social Sciences & Humanities > Arts and Humanities (miscellaneous)
Social Sciences & Humanities > General Psychology
Uncontrolled Keywords:General Psychology, Arts and Humanities (miscellaneous), General Medicine, Statistics and Probability
Language:English
Date:1 November 2019
Deposited On:12 May 2023 13:42
Last Modified:29 Jun 2024 01:36
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:0007-1102
OA Status:Closed
Publisher DOI:https://doi.org/10.1111/bmsp.12158
PubMed ID:30756379
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  • : FunderDeutsche Forschungsgemeinschaft
  • : Grant ID
  • : Project Title