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Paek, Insu; Lin, Zhongtian; Chalmers, Robert Philip – Educational and Psychological Measurement, 2023
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori…
Descriptors: Models, Item Response Theory, Test Items, Intervals
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
Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – Measurement: Interdisciplinary Research and Perspectives, 2020
Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychological measurement. When normality is assumed, asymmetry in the actual latent ability distribution has been shown to result in extraction of spurious…
Descriptors: Item Response Theory, Ability, Statistical Distributions, Sample Size
Sengul Avsar, Asiye; Tavsancil, Ezel – Educational Sciences: Theory and Practice, 2017
This study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20…
Descriptors: Test Items, Psychometrics, Nonparametric Statistics, Item Response Theory
Peer reviewedRoberts, Dennis M. – Journal of Educational Measurement, 1987
This study examines a score-difference model for the detection of cheating based on the difference between two scores for an examinee: one based on the appropriate scoring key and another based on an alternative, inappropriate key. It argues that the score-difference method could falsely accuse students as cheaters. (Author/JAZ)
Descriptors: Answer Keys, Cheating, Mathematical Models, Multiple Choice Tests
Wang, Xiang Bo – College Board, 2007
This research examines the effect of increased testing time by comparing the four performance indices of randomly equivalent examinee subpopulations on sections of similar content and difficulty administered at different times on three SAT administrations. A variety of analyses were used in this study and found no evidence that the current SAT…
Descriptors: College Entrance Examinations, Thinking Skills, High School Students, Test Length
Wingersky, Marilyn S.; Lord, Frederic M. – 1983
The sampling errors of maximum likelihood estimates of item-response theory parameters are studied in the case where both people and item parameters are estimated simultaneously. A check on the validity of the standard error formulas is carried out. The effect of varying sample size, test length, and the shape of the ability distribution is…
Descriptors: Error of Measurement, Estimation (Mathematics), Item Banks, Latent Trait Theory
Rizavi, Saba; Hariharan, Swaminathan – Online Submission, 2001
The advantages that computer adaptive testing offers over linear tests have been well documented. The Computer Adaptive Test (CAT) design is more efficient than the Linear test design as fewer items are needed to estimate an examinee's proficiency to a desired level of precision. In the ideal situation, a CAT will result in examinees answering…
Descriptors: Guessing (Tests), Test Construction, Test Length, Computer Assisted Testing

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