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Sauder, Derek; DeMars, Christine – Applied Measurement in Education, 2020
We used simulation techniques to assess the item-level and familywise Type I error control and power of an IRT item-fit statistic, the "S-X"[superscript 2]. Previous research indicated that the "S-X"[superscript 2] has good Type I error control and decent power, but no previous research examined familywise Type I error control.…
Descriptors: Item Response Theory, Test Items, Sample Size, Test Length
Raborn, Anthony W.; Leite, Walter L.; Marcoulides, Katerina M. – Educational and Psychological Measurement, 2020
This study compares automated methods to develop short forms of psychometric scales. Obtaining a short form that has both adequate internal structure and strong validity with respect to relationships with other variables is difficult with traditional methods of short-form development. Metaheuristic algorithms can select items for short forms while…
Descriptors: Test Construction, Automation, Heuristics, Mathematics
Lim, Euijin; Lee, Won-Chan – Applied Measurement in Education, 2020
The purpose of this study is to address the necessity of subscore equating and to evaluate the performance of various equating methods for subtests. Assuming the random groups design and number-correct scoring, this paper analyzed real data and simulated data with four study factors including test dimensionality, subtest length, form difference in…
Descriptors: Equated Scores, Test Length, Test Format, Difficulty Level
Benton, Tom – Research Matters, 2021
Computer adaptive testing is intended to make assessment more reliable by tailoring the difficulty of the questions a student has to answer to their level of ability. Most commonly, this benefit is used to justify the length of tests being shortened whilst retaining the reliability of a longer, non-adaptive test. Improvements due to adaptive…
Descriptors: Risk, Item Response Theory, Computer Assisted Testing, Difficulty Level
Guo, Hongwen; Dorans, Neil J. – ETS Research Report Series, 2019
The Mantel-Haenszel delta difference (MH D-DIF) and the standardized proportion difference (STD P-DIF) are two observed-score methods that have been used to assess differential item functioning (DIF) at Educational Testing Service since the early 1990s. Latentvariable approaches to assessing measurement invariance at the item level have been…
Descriptors: Test Bias, Educational Testing, Statistical Analysis, Item Response Theory
Hula, William D.; Fergadiotis, Gerasimos; Swiderski, Alexander M.; Silkes, JoAnn P.; Kellough, Stacey – Journal of Speech, Language, and Hearing Research, 2020
Purpose: The purpose of this study was to verify the equivalence of 2 alternate test forms with nonoverlapping content generated by an item response theory (IRT)--based computer-adaptive test (CAT). The Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996) was utilized as an item bank in a prospective, independent…
Descriptors: Adaptive Testing, Computer Assisted Testing, Severity (of Disability), Aphasia
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
Arikan, Serkan; Aybek, Eren Can – Educational Measurement: Issues and Practice, 2022
Many scholars compared various item discrimination indices in real or simulated data. Item discrimination indices, such as item-total correlation, item-rest correlation, and IRT item discrimination parameter, provide information about individual differences among all participants. However, there are tests that aim to select a very limited number…
Descriptors: Monte Carlo Methods, Item Analysis, Correlation, Individual Differences
Ziying Li; A. Corinne Huggins-Manley; Walter L. Leite; M. David Miller; Eric A. Wright – Educational and Psychological Measurement, 2022
The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…
Descriptors: Sequential Approach, Item Response Theory, Data, Simulation
Xu, Peng; Desmarais, Michel C. – International Educational Data Mining Society, 2018
In most contexts of student skills assessment, whether the test material is administered by the teacher or within a learning environment, there is a strong incentive to minimize the number of questions or exercises administered in order to get an accurate assessment. This minimization objective can be framed as a Q-matrix design problem: given a…
Descriptors: Test Items, Accuracy, Test Construction, Skills
Tulek, Onder Kamil; Kose, Ibrahim Alper – Eurasian Journal of Educational Research, 2019
Purpose: This research investigates Tests that include DIF items and which are purified from DIF items. While doing this, the ability estimations and purified DIF items are compared to understand whether there is a correlation between the estimations. Method: The researcher used to R 3.4.1 in order to compare the items and after this situation;…
Descriptors: Test Items, Item Analysis, Item Response Theory, Test Length
Köse, Alper; Dogan, C. Deha – International Journal of Evaluation and Research in Education, 2019
The aim of this study was to examine the precision of item parameter estimation in different sample sizes and test lengths under three parameter logistic model (3PL) item response theory (IRT) model, where the trait measured by a test was not normally distributed or had a skewed distribution. In the study, number of categories (1-0), and item…
Descriptors: Statistical Bias, Item Response Theory, Simulation, Accuracy
Lu, Ru; Guo, Hongwen; Dorans, Neil J. – ETS Research Report Series, 2021
Two families of analysis methods can be used for differential item functioning (DIF) analysis. One family is DIF analysis based on observed scores, such as the Mantel-Haenszel (MH) and the standardized proportion-correct metric for DIF procedures; the other is analysis based on latent ability, in which the statistic is a measure of departure from…
Descriptors: Robustness (Statistics), Weighted Scores, Test Items, Item Analysis
Hill, Andrew P.; Donachie, Tracy – Journal of Psychoeducational Assessment, 2020
The measurement of perfectionistic cognitions has recently caused disagreement among researchers. Flett, Hewitt, Blankstein, and Gray proposed that perfectionistic cognitions are unidimensional. However, after re-examining the factor structure of the instrument used to measure perfectionistic automatic thoughts (Perfectionism Cognitions Inventory…
Descriptors: Factor Structure, Test Length, Cognitive Processes, Personality Traits
Luo, Xiao; Wang, Xinrui – International Journal of Testing, 2019
This study introduced dynamic multistage testing (dy-MST) as an improvement to existing adaptive testing methods. dy-MST combines the advantages of computerized adaptive testing (CAT) and computerized adaptive multistage testing (ca-MST) to create a highly efficient and regulated adaptive testing method. In the test construction phase, multistage…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Construction, Psychometrics

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