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Lee, Woo-yeol; Cho, Sun-Joo – Journal of Educational Measurement, 2017
Cross-level invariance in a multilevel item response model can be investigated by testing whether the within-level item discriminations are equal to the between-level item discriminations. Testing the cross-level invariance assumption is important to understand constructs in multilevel data. However, in most multilevel item response model…
Descriptors: Test Items, Item Response Theory, Item Analysis, Simulation
Wheadon, Christopher – Research Papers in Education, 2013
This paper describes how item response theory (IRT) methods of test-equating could be applied to the maintenance of public examination standards in England. IRT methods of test-equating have been sparingly applied to the main public examinations in England, namely the General Certificate of Secondary Education (GCSE), the equivalent of a school…
Descriptors: Test Theory, Foreign Countries, Exit Examinations, Item Response Theory
Gao, Furong; Chen, Lisue – Applied Measurement in Education, 2005
Through a large-scale simulation study, this article compares item parameter estimates obtained by the marginal maximum likelihood estimation (MMLE) and marginal Bayes modal estimation (MBME) procedures in the 3-parameter logistic model. The impact of different prior specifications on the MBME estimates is also investigated using carefully…
Descriptors: Simulation, Computation, Bayesian Statistics, Item Analysis
Peer reviewedSwaminathan, Hariharan; Gifford, Janice A. – Journal of Educational Statistics, 1982
Bayesian estimation procedures based on a hierarchical model for estimating parameters in the Rasch model are described. It is shown that the Bayesian procedures result in estimates with superior statistical characteristics. (Author/JKS)
Descriptors: Bayesian Statistics, Comparative Analysis, Estimation (Mathematics), Item Analysis
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
Mislevy, Robert J. – 1986
The precision of item parameter estimates can be increased by taking advantage of dependencies between the latent proficiency variable and auxiliary examinee variables such as age, courses taken, and years of schooling. Score gains roughly equivalent to two to six additional item responses can be expected in typical educational and psychological…
Descriptors: Bayesian Statistics, Estimation (Mathematics), Information Utilization, Item Analysis
Yen, Wendy M. – 1982
The three-parameter logistic model discussed was used by CTB/McGraw-Hill in the development of the Comprehensive Tests of Basic Skills, Form U (CTBS/U) and the Test of Cognitive Skills (TCS), published in the fall of 1981. The development, standardization, and scoring of the tests are described, particularly as these procedures were influenced by…
Descriptors: Achievement Tests, Bayesian Statistics, Cognitive Processes, Data Collection
Vale, C. David; And Others – 1981
A simulation study to determine appropriate linking methods for adaptive testing items was designed. Three basic data sets for responses were created. These were randomly sampled, systematically sampled, and selected data sets. The evaluative criteria used were fidelity of parameter estimation, asymptotic ability estimates, root-mean-square error…
Descriptors: Adaptive Testing, Aptitude Tests, Armed Forces, Bayesian Statistics
Mislevy, Robert J. – 1987
Standard procedures for estimating item parameters in Item Response Theory models make no use of auxiliary information about test items, such as their format or content, or the skills they require for solution. This paper describes a framework for exploiting this information, thereby enhancing the precision and stability of item parameter…
Descriptors: Bayesian Statistics, Difficulty Level, Estimation (Mathematics), Intermediate Grades
Buhr, Dianne C.; Algina, James – 1986
The focus of this study is on the estimation procedures implemented in BILOG, a computer program. One purpose is to compare the item parameter estimates produced by various procedures available in BILOG. Four different models are used: the one, two, and three parameter model and a three parameter model with common guessing parameters. The results…
Descriptors: Ability, Bayesian Statistics, Comparative Analysis, Computer Oriented Programs
Peer reviewedAnd Others; Hambleton, Ronald K. – Review of Educational Research, 1978
Topics concerning latent trait theory are addressed: (1) dimensionality of latent space, local independence, and item characteristic curves; (2) models--equations, parameter estimation, testing assumptions, and goodness of fit, (3) applications test developments, item bias, tailored testing and equating; and (4) advantages over classical…
Descriptors: Ability, Bayesian Statistics, Goodness of Fit, Item Analysis
Warm, Thomas A. – 1978
This primer is an introduction to item response theory (also called item characteristic curve theory, or latent trait theory) as it is used most commonly--for scoring multiple choice achievement or aptitude tests. Written for the testing practitioner with minimum training in statistics and psychometrics, it presents and illustrates the basic…
Descriptors: Ability Identification, Achievement Tests, Adaptive Testing, Aptitude Tests

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