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Direct linkSinharay, Sandip; Johnson, Matthew S. – Journal of Educational and Behavioral Statistics, 2021
Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2021
Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
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 Four hitherto-unpublished real data examples are provided to…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 Four hitherto-unpublished real data examples are provided to…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 – 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
Sinharay, Sandip; Johnson, Matthew S.; Williamson, David M. – Journal of Educational and Behavioral Statistics, 2003
Item families, which are groups of related items, are becoming increasingly popular in complex educational assessments. For example, in automatic item generation (AIG) systems, a test may consist of multiple items generated from each of a number of item models. Item calibration or scoring for such an assessment requires fitting models that can…
Descriptors: Test Items, Markov Processes, Educational Testing, Probability
