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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2022
Takers of educational tests often receive proficiency levels instead of or in addition to scaled scores. For example, proficiency levels are reported for the Advanced Placement (AP®) and U.S. Medical Licensing examinations. Technical difficulties and other unforeseen events occasionally lead to missing item scores and hence to incomplete data on…
Descriptors: Computation, Data Analysis, Educational Testing, Accuracy
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Johnson, Matthew S.; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2020
One common score reported from diagnostic classification assessments is the vector of posterior means of the skill mastery indicators. As with any assessment, it is important to derive and report estimates of the reliability of the reported scores. After reviewing a reliability measure suggested by Templin and Bradshaw, this article suggests three…
Descriptors: Reliability, Probability, Skill Development, Classification
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2018
Wollack, Cohen, and Eckerly suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This article suggests two modifications of the EDI for…
Descriptors: Deception, Identification, Testing Problems, Cheating
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Sinharay, Sandip; Johnson, Matthew S. – Educational and Psychological Measurement, 2017
In a pioneering research article, Wollack and colleagues suggested the "erasure detection index" (EDI) to detect test tampering. The EDI can be used with or without a continuity correction and is assumed to follow the standard normal distribution under the null hypothesis of no test tampering. When used without a continuity correction,…
Descriptors: Deception, Identification, Testing Problems, Error of Measurement
Sinharay, Sandip – Grantee Submission, 2017
Wollack, Cohen, and Eckerly (2015) suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly (2017) extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This paper suggests two modifications of…
Descriptors: Deception, Identification, Testing Problems, Cheating
Sinharay, Sandip – Grantee Submission, 2018
Tatsuoka (1984) suggested several extended caution indices and their standardized versions that have been used as person-fit statistics by researchers such as Drasgow, Levine, and McLaughlin (1987), Glas and Meijer (2003), and Molenaar and Hoijtink (1990). However, these indices are only defined for tests with dichotomous items. This paper extends…
Descriptors: Test Format, Goodness of Fit, Item Response Theory, Error Patterns
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2015
The maximum likelihood estimate (MLE) of the ability parameter of an item response theory model with known item parameters was proved to be asymptotically normally distributed under a set of regularity conditions for tests involving dichotomous items and a unidimensional ability parameter (Klauer, 1990; Lord, 1983). This article first considers…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Test Items, Ability
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Sinharay, Sandip – Journal of Educational Measurement, 2016
De la Torre and Deng suggested a resampling-based approach for person-fit assessment (PFA). The approach involves the use of the [math equation unavailable] statistic, a corrected expected a posteriori estimate of the examinee ability, and the Monte Carlo (MC) resampling method. The Type I error rate of the approach was closer to the nominal level…
Descriptors: Sampling, Research Methodology, Error Patterns, Monte Carlo Methods
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Sinharay, Sandip – Applied Measurement in Education, 2017
Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…
Descriptors: Nonparametric Statistics, Goodness of Fit, Simulation, Comparative Analysis
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2016
Meijer and van Krimpen-Stoop noted that the number of person-fit statistics (PFSs) that have been designed for computerized adaptive tests (CATs) is relatively modest. This article partially addresses that concern by suggesting three new PFSs for CATs. The statistics are based on tests for a change point and can be used to detect an abrupt change…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Goodness of Fit
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2015
Person-fit assessment may help the researcher to obtain additional information regarding the answering behavior of persons. Although several researchers examined person fit, there is a lack of research on person-fit assessment for mixed-format tests. In this article, the lz statistic and the ?2 statistic, both of which have been used for tests…
Descriptors: Test Format, Goodness of Fit, Item Response Theory, Bayesian Statistics
Guo, Hongwen; Sinharay, Sandip – Educational Testing Service, 2011
Nonparametric, or kernel, estimation of item response curve (IRC) is a concern theoretically and operationally. Accuracy of this estimation, often used in item analysis in testing programs, is biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. In this study, we investigate…
Descriptors: Error of Measurement, Nonparametric Statistics, Item Response Theory, Computation
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Sinharay, Sandip; Dorans, Neil J. – Journal of Educational and Behavioral Statistics, 2010
The Mantel-Haenszel (MH) procedure (Mantel and Haenszel) is a popular method for estimating and testing a common two-factor association parameter in a 2 x 2 x K table. Holland and Holland and Thayer described how to use the procedure to detect differential item functioning (DIF) for tests with dichotomously scored items. Wang, Bradlow, Wainer, and…
Descriptors: Test Bias, Statistical Analysis, Computation, Bayesian Statistics
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Puhan, Gautam; Sinharay, Sandip; Haberman, Shelby; Larkin, Kevin – Applied Measurement in Education, 2010
Will subscores provide additional information than what is provided by the total score? Is there a method that can estimate more trustworthy subscores than observed subscores? To answer the first question, this study evaluated whether the true subscore was more accurately predicted by the observed subscore or total score. To answer the second…
Descriptors: Licensing Examinations (Professions), Scores, Computation, Methods
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Sinharay, Sandip; Dorans, Neil J.; Grant, Mary C.; Blew, Edwin O. – Journal of Educational and Behavioral Statistics, 2009
Test administrators often face the challenge of detecting differential item functioning (DIF) with samples of size smaller than that recommended by experts. A Bayesian approach can incorporate, in the form of a prior distribution, existing information on the inference problem at hand, which yields more stable estimation, especially for small…
Descriptors: Test Bias, Computation, Bayesian Statistics, Data
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