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Sinharay, Sandip – Journal of Educational Measurement, 2023
Technical difficulties and other unforeseen events occasionally lead to incomplete data on educational tests, which necessitates the reporting of imputed scores to some examinees. While there exist several approaches for reporting imputed scores, there is a lack of any guidance on the reporting of the uncertainty of imputed scores. In this paper,…
Descriptors: Evaluation Methods, Scores, Standardized Tests, Simulation
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2022
Administrative problems such as computer malfunction and power outage occasionally lead to missing item scores, and hence to incomplete data, on credentialing tests such as the United States Medical Licensing examination. Feinberg compared four approaches for reporting pass-fail decisions to the examinees with incomplete data on credentialing…
Descriptors: Testing Problems, High Stakes Tests, Credentials, Test Items
Gorney, Kylie; Wollack, James A.; Sinharay, Sandip; Eckerly, Carol – Journal of Educational and Behavioral Statistics, 2023
Any time examinees have had access to items and/or answers prior to taking a test, the fairness of the test and validity of test score interpretations are threatened. Therefore, there is a high demand for procedures to detect both compromised items (CI) and examinees with preknowledge (EWP). In this article, we develop a procedure that uses item…
Descriptors: Scores, Test Validity, Test Items, Prior Learning
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2021
Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data…
Descriptors: Data Analysis, Scores, Educational Assessment, Educational Testing
Sinharay, Sandip – Journal of Educational Measurement, 2018
The value-added method of Haberman is arguably one of the most popular methods to evaluate the quality of subscores. The method is based on the classical test theory and deems a subscore to be of added value if the subscore predicts the corresponding true subscore better than does the total score. Sinharay provided an interpretation of the added…
Descriptors: Scores, Value Added Models, Raw Scores, Item Response Theory
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), score differencing is one of six types of statistical methods used to detect test fraud. In this paper, we suggested the use of Bayes factors (e.g., Kass & Raftery, 1995) for score differencing. A simulation study shows that the suggested approach performs slightly better than an existing frequentist…
Descriptors: Cheating, Deception, Statistical Analysis, Bayesian Statistics
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2019
Test score users often demand the reporting of subscores due to their potential diagnostic, remedial, and instructional benefits. Therefore, there is substantial pressure on testing programs to report subscores. However, professional standards require that subscores have to satisfy minimum quality standards before they can be reported. In this…
Descriptors: Testing, Scores, Item Response Theory, Evaluation Methods
Sinharay, Sandip; Zhang, Mo; Deane, Paul – Applied Measurement in Education, 2019
Analysis of keystroke logging data is of increasing interest, as evident from a substantial amount of recent research on the topic. Some of the research on keystroke logging data has focused on the prediction of essay scores from keystroke logging features, but linear regression is the only prediction method that has been used in this research.…
Descriptors: Scores, Prediction, Writing Processes, Data Analysis
Sinharay, Sandip – Journal of Educational Measurement, 2014
Brennan noted that users of test scores often want (indeed, demand) that subscores be reported, along with total test scores, for diagnostic purposes. Haberman suggested a method based on classical test theory (CTT) to determine if subscores have added value over the total score. One way to interpret the method is that a subscore has added value…
Descriptors: Scores, Test Theory, Classification, Cutting Scores
Sinharay, Sandip – Measurement: Interdisciplinary Research and Perspectives, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
Sinharay, Sandip – Grantee Submission, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), benefitting from item preknowledge is one of the three broad types of test fraud that occur in educational assessments. We use tools from constrained statistical inference to suggest a new statistic that is based on item scores and response times and can be used to detect the examinees who may have…
Descriptors: Scores, Test Items, Reaction Time, Cheating
Sinharay, Sandip; Haberman, Shelby; Boughton, Keith – Educational Measurement: Issues and Practice, 2015
Feinberg and Wainer (2014) provided a simple equation to approximate/predict a subscore's value. The purpose of this note is to point out that their equation is often inaccurate in that it does not always predict a subscore's value correctly. Therefore, the utility of their simple equation is not clear.
Descriptors: Equations (Mathematics), Scores, Prediction, Accuracy
Sinharay, Sandip – Journal of Educational Measurement, 2017
Person-fit assessment (PFA) is concerned with uncovering atypical test performance as reflected in the pattern of scores on individual items on a test. Existing person-fit statistics (PFSs) include both parametric and nonparametric statistics. Comparison of PFSs has been a popular research topic in PFA, but almost all comparisons have employed…
Descriptors: Goodness of Fit, Testing, Test Items, Scores
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2014
Brennan (Brennan, R. L., 2012) noted that users of test scores often want (indeed, demand) that subscores be reported, along with total test scores, for diagnostic purposes. Haberman (Haberman, S. J., 2008) suggested a method based on classical test theory (CTT) to determine if subscores have added value over the total score. According to this…
Descriptors: Scores, Test Theory, Test Interpretation