Literature DB >> 35476176

Item Response Thresholds Models: A General Class of Models for Varying Types of Items.

Gerhard Tutz1.   

Abstract

A comprehensive class of models is proposed that can be used for continuous, binary, ordered categorical and count type responses. The difficulty of items is described by difficulty functions, which replace the item difficulty parameters that are typically used in item response models. They crucially determine the response distribution and make the models very flexible with regard to the range of distributions that are covered. The model class contains several widely used models as the binary Rasch model and the graded response model as special cases, allows for simplifications, and offers a distribution free alternative to count type items. A major strength of the models is that they can be used for mixed item formats, when different types of items are combined to measure abilities or attitudes. It is an immediate consequence of the comprehensive modeling approach that allows that difficulty functions automatically adapt to the response distribution. Basic properties of the model class are shown. Several real data sets are used to illustrate the flexibility of the models.
© 2022. The Author(s).

Entities:  

Keywords:  Rasch model; graded response model; item response theory; latent trait models; thresholds model

Year:  2022        PMID: 35476176     DOI: 10.1007/s11336-022-09865-7

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  7 in total

1.  A general framework and an R package for the detection of dichotomous differential item functioning.

Authors:  David Magis; Sébastien Béland; Francis Tuerlinckx; Paul De Boeck
Journal:  Behav Res Methods       Date:  2010-08

2.  A penalty approach to differential item functioning in Rasch models.

Authors:  Gerhard Tutz; Gunther Schauberger
Journal:  Psychometrika       Date:  2013-12-03       Impact factor: 2.500

3.  A generalized item response tree model for psychological assessments.

Authors:  Minjeong Jeon; Paul De Boeck
Journal:  Behav Res Methods       Date:  2016-09

4.  Mountain or Molehill? A Simulation Study on the Impact of Response Styles.

Authors:  Hansjörg Plieninger
Journal:  Educ Psychol Meas       Date:  2016-03-18       Impact factor: 2.821

5.  Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

Authors:  Shelby J Haberman; Sandip Sinharay; Kyong Hee Chon
Journal:  Psychometrika       Date:  2012-12-14       Impact factor: 2.500

6.  Different approaches to modeling response styles in divide-by-total item response theory models (part 1): A model integration.

Authors:  Mirka Henninger; Thorsten Meiser
Journal:  Psychol Methods       Date:  2020-10

7.  Semiparametric regression during 2003-2007.

Authors:  David Ruppert; M P Wand; Raymond J Carroll
Journal:  Electron J Stat       Date:  2009-01-01       Impact factor: 1.125

  7 in total
  1 in total

1.  Flexible Item Response Models for Count Data: The Count Thresholds Model.

Authors:  Gerhard Tutz
Journal:  Appl Psychol Meas       Date:  2022-08-07
  1 in total

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