The robust estimation of examinee ability based on the four-parameter logistic model when guessing and carelessness responses exist

Xiaozhu Jian, Dai Buyun and Deng Yuanping

PLOS ONE, 2021, vol. 16, issue 4, 1-16

Abstract: The three-parameter Logistic model (3PLM) and the four-parameter Logistic model (4PLM) have been proposed to reduce biases in cases of response disturbances, including random guessing and carelessness. However, they could also influence the examinees who do not guess or make careless errors. This paper proposes a new approach to solve this problem, which is a robust estimation based on the 4PLM (4PLM-Robust), involving a critical-probability guessing parameter and a carelessness parameter. This approach is compared with the 2PLM-MLE(two-parameter Logistic model and a maximum likelihood estimator), the 3PLM-MLE, the 4PLM-MLE, the Biweight estimation and the Huber estimation in terms of bias using an example and three simulation studies. The results show that the 4PLM-Robust is an effective method for robust estimation, and its calculation is simpler than the Biweight estimation and the Huber estimation.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0250268

DOI: 10.1371/journal.pone.0250268

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