Literature DB >> 26208813

A generalized item response tree model for psychological assessments.

Minjeong Jeon1, Paul De Boeck2.   

Abstract

A new item response theory (IRT) model with a tree structure has been introduced for modeling item response processes with a tree structure. In this paper, we present a generalized item response tree model with a flexible parametric form, dimensionality, and choice of covariates. The utilities of the model are demonstrated with two applications in psychological assessments for investigating Likert scale item responses and for modeling omitted item responses. The proposed model is estimated with the freely available R package flirt (Jeon et al., 2014b).

Keywords:  IRT; IRTree; Item response process; Likert scale; Omitted responses; Tree; flirt

Mesh:

Year:  2016        PMID: 26208813     DOI: 10.3758/s13428-015-0631-y

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  21 in total

1.  A General Unfolding IRT Model for Multiple Response Styles.

Authors:  Chen-Wei Liu; Wen-Chung Wang
Journal:  Appl Psychol Meas       Date:  2018-04-16

2.  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

3.  Unfolding IRT Models for Likert-Type Items With a Don't Know Option.

Authors:  Chen-Wei Liu; Wen-Chung Wang
Journal:  Appl Psychol Meas       Date:  2016-08-20

4.  A Sequential IRT Model for Multiple-Choice Items and a Multidimensional Extension.

Authors:  Sien Deng; Daniel M Bolt
Journal:  Appl Psychol Meas       Date:  2016-02-15

5.  Applying Unidimensional Models for Semiordered Data to Scale Data With Neutral Responses.

Authors:  Sophie Cohn; Anne Corinne Huggins-Manley
Journal:  Educ Psychol Meas       Date:  2019-07-11       Impact factor: 2.821

6.  Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

Authors:  Dylan Molenaar; Paul de Boeck
Journal:  Psychometrika       Date:  2018-02-01       Impact factor: 2.500

7.  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

8.  Contextual Responses to Affirmative and/or Reversed-Worded Items.

Authors:  Ulf Böckenholt
Journal:  Psychometrika       Date:  2019-09-04       Impact factor: 2.500

9.  Modeling Intensive Polytomous Time-Series Eye-Tracking Data: A Dynamic Tree-Based Item Response Model.

Authors:  Sun-Joo Cho; Sarah Brown-Schmidt; Paul De Boeck; Jianhong Shen
Journal:  Psychometrika       Date:  2020-02-21       Impact factor: 2.500

10.  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

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