Assessing Fit of the Lognormal Model for Response Times

Sinharay, Sandip; Rijn, Peter W. van

doi:10.3102/1076998620911935

Cited by 6 publications

(1 citation statement)

References 63 publications

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“…Finger and Chee (2009) showed how one can use factor analysis to obtain the MMLEs of the item parameters of the LNMRT when it is used as a stand-alone model, as in van der Linden (2006). The R package lavaan (Rosseel, 2012), which is used to perform factor analysis and structural equation modeling (SEM), can be used to estimate the item parameters of the LNMRT, as shown by Sinharay and van Rijn (2020).…”

Section: The Lognormal Model For Response Timesmentioning

confidence: 99%

Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

Sinharay

2021

Open Education Studies

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There is a growing interest in approaches based on latent-variable models for detecting fraudulent behavior on educational tests. Wollack and Schoenig (2018) noted the presence of five types of statistical/psychometric approaches to detect the three broad types of test fraud that occur in educational tests. This paper includes a brief review of the five types of statistical/psychometric approaches mentioned by Wollack and Schoenig (2018). This paper then includes a more detailed review of the recent approaches for detecting test fraud using both item scores and response times—all of these approaches are based on latent-variable models. A real data example demonstrates the use of two of the approaches.

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Section: The Lognormal Model For Response Timesmentioning

confidence: 99%

Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

Sinharay

2021

Open Education Studies

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Semiparametric Factor Analysis for Item-Level Response Time Data

Liu

Wang

2022

Psychometrika

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Parallel Optimal Calibration of Mixed-Format Items for Achievement Tests

Miller,

Fackle-Fornius

2024

Psychometrika

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When large achievement tests are conducted regularly, items need to be calibrated before being used as operational items in a test. Methods have been developed to optimally assign pretest items to examinees based on their abilities. Most of these methods, however, are intended for situations where examinees arrive sequentially to be assigned to calibration items. In several calibration tests, examinees take the test simultaneously or in parallel. In this article, we develop an optimal calibration design tailored for such parallel test setups. Our objective is both to investigate the efficiency gain of the method as well as to demonstrate that this method can be implemented in real calibration scenarios. For the latter, we have employed this method to calibrate items for the Swedish national tests in Mathematics. In this case study, like in many real test situations, items are of mixed format and the optimal design method needs to handle that. The method we propose works for mixed-format tests and accounts for varying expected response times. Our investigations show that the proposed method considerably enhances calibration efficiency.

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Assessing Fit of the Lognormal Model for Response Times

Cited by 6 publications

References 63 publications

Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

Semiparametric Factor Analysis for Item-Level Response Time Data

Parallel Optimal Calibration of Mixed-Format Items for Achievement Tests

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