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Wyse, Adam E.; McBride, James R. – Measurement: Interdisciplinary Research and Perspectives, 2022
A common practical challenge is how to assign ability estimates to all incorrect and all correct response patterns when using item response theory (IRT) models and maximum likelihood estimation (MLE) since ability estimates for these types of responses equal -8 or +8. This article uses a simulation study and data from an operational K-12…
Descriptors: Scores, Adaptive Testing, Computer Assisted Testing, Test Length
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Ho, Tsung-Han; Dodd, Barbara G. – Applied Measurement in Education, 2012
In this study we compared five item selection procedures using three ability estimation methods in the context of a mixed-format adaptive test based on the generalized partial credit model. The item selection procedures used were maximum posterior weighted information, maximum expected information, maximum posterior weighted Kullback-Leibler…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
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Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length
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Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R. – Educational and Psychological Measurement, 2006
The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…
Descriptors: Classification, Computation, Simulation, Item Response Theory
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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
De Ayala, R. J.; And Others – 1995
Expected a posteriori has a number of advantages over maximum likelihood estimation or maximum a posteriori (MAP) estimation methods. These include ability estimates (thetas) for all response patterns, less regression towards the mean than MAP ability estimates, and a lower average squared error. R. D. Bock and R. J. Mislevy (1982) state that the…
Descriptors: Adaptive Testing, Bayesian Statistics, Error of Measurement, Estimation (Mathematics)
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Green, Bert F. – 2002
Maximum likelihood and Bayesian estimates of proficiency, typically used in adaptive testing, use item weights that depend on test taker proficiency to estimate test taker proficiency. In this study, several methods were explored through computer simulation using fixed item weights, which depend mainly on the items difficulty. The simpler scores…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
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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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Wang, Tianyou; Hanson, Bradley A.; Lau, Che-Ming A. – Applied Psychological Measurement, 1999
Extended the use of a beta prior in trait estimation to the maximum expected a posteriori (MAP) method of Bayesian estimation. This new method, essentially unbiased MAP, was compared with MAP, essentially unbiased expected a posteriori, weighted likelihood, and maximum-likelihood estimation methods. The new method significantly reduced bias in…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Estimation (Mathematics)
Samejima, Fumiko – 1981
In the methods and approaches developed for estimating the operating characteristics of the discrete item responses, the maximum likelihood estimate of the examinee based upon the "Old Test" has an important role. When Old Test does not provide a sufficient amount of test information for the upper and lower part of the ability interval,…
Descriptors: Academic Ability, Adaptive Testing, Bayesian Statistics, Error Patterns
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Lin, Miao-Hsiang; Hsiung, Chao A. – Psychometrika, 1994
Two simple empirical approximate Bayes estimators are introduced for estimating domain scores under binomial and hypergeometric distributions respectively. Criteria are established regarding use of these functions over maximum likelihood estimation counterparts. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computation, Equations (Mathematics)
Rosso, Martin A.; Reckase, Mark D. – 1981
The overall purpose of this research was to compare a maximum likelihood based tailored testing procedure to a Bayesian tailored testing procedure. The results indicated that both tailored testing procedures produced equally reliable ability estimates. Also an analysis of test length indicated that reasonable ability estimates could be obtained…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing
Glas, Cees A. W.; van der Linden, Wim J. – 2001
To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Costs
Kirisci, Levent; Hsu, Tse-Chi – 1988
The predictive analysis approach to adaptive testing originated in the idea of statistical predictive analysis suggested by J. Aitchison and I.R. Dunsmore (1975). The adaptive testing model proposed is based on parameter-free predictive distribution. Aitchison and Dunsmore define statistical prediction analysis as the use of data obtained from an…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Item Analysis
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