An Iterative Scale Purification Procedure on lz for the Detection of Aberrant Responses
Journal article
Qiu, Xuelan, Huang, Sheng-Yun, Wang, Wen-Chung and Wang, You-Gan. (2024). An Iterative Scale Purification Procedure on lz for the Detection of Aberrant Responses. Multivariate Behavioral Research. 59(1), pp. 62-77. https://doi.org/10.1080/00273171.2023.2211564
Authors | Qiu, Xuelan, Huang, Sheng-Yun, Wang, Wen-Chung and Wang, You-Gan |
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Abstract | Many person-fit statistics have been proposed to detect aberrant response behaviors (e.g., cheating, guessing). Among them, lz is one of the most widely used indices. The computation of lz assumes the item and person parameters are known. In reality, they often have to be estimated from data. The better the estimation, the better lz will perform. When aberrant behaviors occur, the person and item parameter estimations are inaccurate, which in turn degrade the performance of lz. In this study, an iterative procedure was developed to attain more accurate person parameter estimates for improved performance of lz. A series of simulations were conducted to evaluate the iterative procedure under two conditions of item parameters, known and unknown, and three aberrant response styles of difficulty-sharing cheating, random-sharing cheating, and random guessing. The results demonstrated the superiority of the iterative procedure over the non-iterative one in maintaining control of Type-I error rates and improving the power of detecting aberrant responses. The proposed procedure was applied to a high-stake intelligence test. |
Keywords | person-fit statistics; lz; scale purification; aberrant behaviors; cheating; guessing; item response theory |
Year | 01 Jan 2024 |
Journal | Multivariate Behavioral Research |
Journal citation | 59 (1), pp. 62-77 |
Publisher | Routledge |
ISSN | 1532-7906 |
Digital Object Identifier (DOI) | https://doi.org/10.1080/00273171.2023.2211564 |
Web address (URL) | https://www.tandfonline.com/doi/full/10.1080/00273171.2023.2211564 |
Open access | Open access |
Research or scholarly | Research |
Page range | 62-77 |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
01 Jun 2023 | |
Publication process dates | |
Deposited | 13 Aug 2024 |
Additional information | © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC |
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. | |
Place of publication | United States |
https://acuresearchbank.acu.edu.au/item/90w8q/an-iterative-scale-purification-procedure-on-lz-for-the-detection-of-aberrant-responses
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Publisher's version
OA_Qiu_2023_An_Iterative_Scale_Purification_Procedure_on.pdf | |
License: CC BY-NC-ND 4.0 | |
File access level: Open |
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