Item Response Models in Computerized Adaptive Testing: A Simulation Study

2014 ◽  
pp. 552-565 ◽  
Author(s):  
Maria Eugénia Ferrão ◽  
Paula Prata
Keyword(s):  
Item Response ◽  
Simulation Study ◽  
Computerized Adaptive Testing ◽  
Adaptive Testing ◽  
Response Models ◽  
Item Response Models

scholarly journals On the complementarity of classical test theory and item response models: item difficulty estimates and computerized adaptive testing

2015 ◽  
Vol 23 (88) ◽  
pp. 593-610
Author(s):  
Patrícia Costa ◽  
Maria Eugénia Ferrão
Keyword(s):  
Item Response ◽  
Computerized Adaptive Testing ◽  
Item Difficulty ◽  
Classical Test Theory ◽  
Adaptive Testing ◽  
Test Theory ◽  
Partial Credit Model ◽  
Response Models ◽  
Item Response Models ◽  
Classical Test

This study aims to provide statistical evidence of the complementarity between classical test theory and item response models for certain educational assessment purposes. Such complementarity might support, at a reduced cost, future development of innovative procedures for item calibration in adaptive testing. Classical test theory and the generalized partial credit model are applied to tests comprising multiple choice, short answer, completion, and open response items scored partially. Datasets are derived from the tests administered to the Portuguese population of students enrolled in the 4th and 6th grades. The results show a very strong association between the estimates of difficulty obtained from classical test theory and item response models, corroborating the statistical theory of mental testing.

scholarly journals Robust Haebara Linking for Many Groups: Performance in the Case of Uniform DIF

Psych ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 155-173
Author(s):  
Alexander Robitzsch
Keyword(s):  
Present Article ◽  
Item Response ◽  
Empirical Research ◽  
Simulation Study ◽  
Response Models ◽  
Item Response Models ◽  
Slight Extension ◽  
Unbiased Estimates ◽  
Pisa Data ◽  
Limiting Case

The comparison of group means in item response models constitutes an important issue in empirical research. The present article discusses a slight extension of the robust Haebara linking approach of He and Cui by proposing a flexible class of robust Haebara linking functions for comparisons of many groups. These robust linking functions are robust against violations of invariance. In this article, we investigate the performance of robust Haebara linking in the presence of uniform DIF effects. In an analytical derivation, it is shown that the robust Haebara linking approach provides unbiased estimates of group means in the limiting case p=0. In a simulation study, it is demonstrated that the proposed variant of the Haebara linking approach outperforms existing implementations of Haebara linking to some extent. In an empirical application using PISA data, it is illustrated that country means can be sensitive to the choice of linking functions.

scholarly journals Improving Measurement Precision in Experimental Psychopathology Using Item Response Theory

2019 ◽  
Vol 80 (4) ◽  
pp. 695-725
Author(s):  
Leah M. Feuerstahler ◽  
Niels Waller ◽  
Angus MacDonald
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Computerized Adaptive Testing ◽  
Cognitive Task ◽  
Working Memory Capacity ◽  
Response Theory ◽  
Response Models ◽  
Item Response Models ◽  
Experimental Psychopathology ◽  
Assessment Tasks

Although item response models have grown in popularity in many areas of educational and psychological assessment, there are relatively few applications of these models in experimental psychopathology. In this article, we explore the use of item response models in the context of a computerized cognitive task designed to assess visual working memory capacity in people with psychosis as well as healthy adults. We begin our discussion by describing how item response theory can be used to evaluate and improve unidimensional cognitive assessment tasks in various examinee populations. We then suggest how computerized adaptive testing can be used to improve the efficiency of cognitive task administration. Finally, we explore how these ideas might be extended to multidimensional item response models that better represent the complex response processes underlying task performance in psychopathological populations.

scholarly journals Robust Haebara Linking for Many Groups in the Case of Partial Invariance

2020 ◽  
Author(s):  
Alexander Robitzsch
Keyword(s):  
Present Article ◽  
Item Response ◽  
Empirical Research ◽  
Simulation Study ◽  
Response Models ◽  
Item Response Models ◽  
Empirical Application ◽  
Response Data ◽  
Partial Invariance ◽  
Pisa Data

The comparison of group means in item response models constitutes an important issue in empirical research. The present article discusses an extension of Haebara linking by proposing a flexible class of robust linking functions for comparisons of many groups. These robust linking functions are particularly suited to item response data that are generated under partial invariance. In a simulation study, it is shown that the newly proposed robust Haebara linking approach outperforms existing approaches of Haebara linking. In an empirical application using PISA data, it is illustrated that country means can be sensitive to the choice of linking functions.

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