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Showing 1 to 15 of 20 results Save | Export
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Ranger, Jochen; Kuhn, Jörg-Tobias; Wolgast, Anett – Journal of Educational Measurement, 2021
Van der Linden's hierarchical model for responses and response times can be used in order to infer the ability and mental speed of test takers from their responses and response times in an educational test. A standard approach for this is maximum likelihood estimation. In real-world applications, the data of some test takers might be partly…
Descriptors: Models, Reaction Time, Item Response Theory, Tests
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Sahin, Alper; Weiss, David J. – Educational Sciences: Theory and Practice, 2015
This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Sample Size, Item Banks
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Tao, Jian; Shi, Ning-Zhong; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2012
For mixed-type tests composed of both dichotomous and polytomous items, polytomous items often yield more information than dichotomous ones. To reflect the difference between the two types of items, polytomous items are usually pre-assigned with larger weights. We propose an item-weighted likelihood method to better assess examinees' ability…
Descriptors: Test Items, Weighted Scores, Maximum Likelihood Statistics, Statistical Bias
MacDonald, George T. – ProQuest LLC, 2014
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Descriptors: Simulation, Item Response Theory, Models, Test Items
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Schuster, Christof; Yuan, Ke-Hai – Journal of Educational and Behavioral Statistics, 2011
Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…
Descriptors: Computation, Item Response Theory, Probability, Maximum Likelihood Statistics
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He, Wei; Wolfe, Edward W. – Educational and Psychological Measurement, 2012
In administration of individually administered intelligence tests, items are commonly presented in a sequence of increasing difficulty, and test administration is terminated after a predetermined number of incorrect answers. This practice produces stochastically censored data, a form of nonignorable missing data. By manipulating four factors…
Descriptors: Individual Testing, Intelligence Tests, Test Items, Test Length
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Zhang, Jinming; Lu, Ting – ETS Research Report Series, 2007
In practical applications of item response theory (IRT), item parameters are usually estimated first from a calibration sample. After treating these estimates as fixed and known, ability parameters are then estimated. However, the statistical inferences based on the estimated abilities can be misleading if the uncertainty of the item parameter…
Descriptors: Item Response Theory, Ability, Error of Measurement, Maximum Likelihood Statistics
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DeMars, Christine – Applied Measurement in Education, 2002
Simulated items from two test forms using joint maximum likelihood estimation (JMLE) and marginal maximum likelihood estimation (MML) in the vertical equating situation (using an anchor test) when data were nonrandomly missing. Under MML, when the different ability parameters of students were not taken into account, the item difficulty parameters…
Descriptors: Ability, Equated Scores, Estimation (Mathematics), Maximum Likelihood Statistics
De Ayala, R. J.; Plake, Barbara S.; Impara, James C.; Kozmicky, Michelle – 2000
This study investigated the effect on examinees' ability estimate under item response theory (IRT) when they are presented an item, have ample time to answer the item, but decide not to respond to the item. Simulation data were modeled on an empirical data set of 25,546 examinees that was calibrated using the 3-parameter logistic model. The study…
Descriptors: Ability, Estimation (Mathematics), Item Response Theory, Maximum Likelihood Statistics
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Wang, Tianyou; Vispoel, Walter P. – Journal of Educational Measurement, 1998
Used simulations of computerized adaptive tests to evaluate results yielded by four commonly used ability estimation methods: maximum likelihood estimation (MLE) and three Bayesian approaches. Results show clear distinctions between MLE and Bayesian methods. (SLD)
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
Yamamoto, Kentaro; Muraki, Eiji – 1991
The extent to which properties of the ability scale and the form of the latent trait distribution influence the estimated item parameters of item response theory (IRT) was investigated using real and simulated data. Simulated data included 5,000 ability values randomly drawn from the standard normal distribution. Real data included the results for…
Descriptors: Ability, Estimation (Mathematics), Graphs, Item Response Theory
Weissman, Alexander – 2003
This study investigated the efficiency of item selection in a computerized adaptive test (CAT), where efficiency was defined in terms of the accumulated test information at an examinee's true ability level. A simulation methodology compared the efficiency of 2 item selection procedures with 5 ability estimation procedures for CATs of 5, 10, 15,…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Maximum Likelihood Statistics
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Nicewander, W. Alan; Thomasson, Gary L. – Applied Psychological Measurement, 1999
Derives three reliability estimates for the Bayes modal estimate (BME) and the maximum-likelihood estimate (MLE) of theta in computerized adaptive tests (CATs). Computes the three reliability estimates and the true reliabilities of both BME and MLE for seven simulated CATs. Results show the true reliabilities for BME and MLE to be nearly identical…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
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Zhang, Jinming – ETS Research Report Series, 2005
Lord's bias function and the weighted likelihood estimation method are effective in reducing the bias of the maximum likelihood estimate of an examinee's ability under the assumption that the true item parameters are known. This paper presents simulation studies to determine the effectiveness of these two methods in reducing the bias when the item…
Descriptors: Statistical Bias, Maximum Likelihood Statistics, Computation, Ability
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Chen, Ssu-Kuang; And Others – Educational and Psychological Measurement, 1997
A simulation study explored the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori (EAP) estimation in computerized adaptive testing based on the rating scale model of D. Andrich (1978). The choice between EAP and MLE for particular situations is discussed. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics)
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