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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
Gu, Zhengguo; Emons, Wilco H. M.; Sijtsma, Klaas – Journal of Educational and Behavioral Statistics, 2021
Clinical, medical, and health psychologists use difference scores obtained from pretest--posttest designs employing the same test to assess intraindividual change possibly caused by an intervention addressing, for example, anxiety, depression, eating disorder, or addiction. Reliability of difference scores is important for interpreting observed…
Descriptors: Test Reliability, Scores, Pretests Posttests, Computation
DeCarlo, Lawrence T. – Journal of Educational Measurement, 2023
A conceptualization of multiple-choice exams in terms of signal detection theory (SDT) leads to simple measures of item difficulty and item discrimination that are closely related to, but also distinct from, those used in classical item analysis (CIA). The theory defines a "true split," depending on whether or not examinees know an item,…
Descriptors: Multiple Choice Tests, Test Items, Item Analysis, Test Wiseness
Gurdil Ege, Hatice; Demir, Ergul – Eurasian Journal of Educational Research, 2020
Purpose: The present study aims to evaluate how the reliabilities computed using a, Stratified a, Angoff-Feldt, and Feldt-Raju estimators may differ when sample size (500, 1000, and 2000) and item type ratio of dichotomous to polytomous items (2:1; 1:1, 1:2) included in the scale are varied. Research Methods: In this study, Cronbach's a,…
Descriptors: Test Format, Simulation, Test Reliability, Sample Size
Leventhal, Brian; Ames, Allison – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Brian Leventhal and Dr. Allison Ames provide an overview of "Monte Carlo simulation studies" (MCSS) in "item response theory" (IRT). MCSS are utilized for a variety of reasons, one of the most compelling being that they can be used when analytic solutions are impractical or nonexistent because…
Descriptors: Item Response Theory, Monte Carlo Methods, Simulation, Test Items
Tang, Xiaodan; Schultz, Matthew – Practical Assessment, Research & Evaluation, 2020
This study aims to examine the potential impacts on repeat examinees' performance by reusing simulation-based items in a high-stakes standardized assessment. We examined change patterns of item scores, ability estimate, score pattern change, response time and compared the performance of repeat examinees who have received repeat items and those who…
Descriptors: Test Items, Repetition, Simulation, Standardized Tests
Ozdemir, Burhanettin; Gelbal, Selahattin – Education and Information Technologies, 2022
The computerized adaptive tests (CAT) apply an adaptive process in which the items are tailored to individuals' ability scores. The multidimensional CAT (MCAT) designs differ in terms of different item selection, ability estimation, and termination methods being used. This study aims at investigating the performance of the MCAT designs used to…
Descriptors: Scores, Computer Assisted Testing, Test Items, Language Proficiency
Ip, Edward H.; Strachan, Tyler; Fu, Yanyan; Lay, Alexandra; Willse, John T.; Chen, Shyh-Huei; Rutkowski, Leslie; Ackerman, Terry – Journal of Educational Measurement, 2019
Test items must often be broad in scope to be ecologically valid. It is therefore almost inevitable that secondary dimensions are introduced into a test during test development. A cognitive test may require one or more abilities besides the primary ability to correctly respond to an item, in which case a unidimensional test score overestimates the…
Descriptors: Test Items, Test Bias, Test Construction, Scores
Kopp, Jason P.; Jones, Andrew T. – Applied Measurement in Education, 2020
Traditional psychometric guidelines suggest that at least several hundred respondents are needed to obtain accurate parameter estimates under the Rasch model. However, recent research indicates that Rasch equating results in accurate parameter estimates with sample sizes as small as 25. Item parameter drift under the Rasch model has been…
Descriptors: Item Response Theory, Psychometrics, Sample Size, Sampling
Yesiltas, Gonca; Paek, Insu – Educational and Psychological Measurement, 2020
A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were…
Descriptors: Simulation, Sample Size, Item Analysis, Scores
Tsaousis, Ioannis; Sideridis, Georgios D.; AlGhamdi, Hannan M. – Journal of Psychoeducational Assessment, 2021
This study evaluated the psychometric quality of a computerized adaptive testing (CAT) version of the general cognitive ability test (GCAT), using a simulation study protocol put forth by Han, K. T. (2018a). For the needs of the analysis, three different sets of items were generated, providing an item pool of 165 items. Before evaluating the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Cognitive Ability
Guo, Hongwen; Zu, Jiyun; Kyllonen, Patrick – ETS Research Report Series, 2018
For a multiple-choice test under development or redesign, it is important to choose the optimal number of options per item so that the test possesses the desired psychometric properties. On the basis of available data for a multiple-choice assessment with 8 options, we evaluated the effects of changing the number of options on test properties…
Descriptors: Multiple Choice Tests, Test Items, Simulation, Test Construction
Monroe, Scott – Journal of Educational and Behavioral Statistics, 2021
This research proposes a new statistic for testing latent variable distribution fit for unidimensional item response theory (IRT) models. If the typical assumption of normality is violated, then item parameter estimates will be biased, and dependent quantities such as IRT score estimates will be adversely affected. The proposed statistic compares…
Descriptors: Item Response Theory, Simulation, Scores, Comparative Analysis
Fu, Jianbin; Feng, Yuling – ETS Research Report Series, 2018
In this study, we propose aggregating test scores with unidimensional within-test structure and multidimensional across-test structure based on a 2-level, 1-factor model. In particular, we compare 6 score aggregation methods: average of standardized test raw scores (M1), regression factor score estimate of the 1-factor model based on the…
Descriptors: Comparative Analysis, Scores, Correlation, Standardized Tests
Andersson, Björn; Xin, Tao – Educational and Psychological Measurement, 2018
In applications of item response theory (IRT), an estimate of the reliability of the ability estimates or sum scores is often reported. However, analytical expressions for the standard errors of the estimators of the reliability coefficients are not available in the literature and therefore the variability associated with the estimated reliability…
Descriptors: Item Response Theory, Test Reliability, Test Items, Scores