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Jones, W. Paul – Educational and Psychological Measurement, 2014
A study in a university clinic/laboratory investigated adaptive Bayesian scaling as a supplement to interpretation of scores on the Mini-IPIP. A "probability of belonging" in categories of low, medium, or high on each of the Big Five traits was calculated after each item response and continued until all items had been used or until a…
Descriptors: Personality Traits, Personality Measures, Bayesian Statistics, Clinics
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Kim, Do-Hong; Lambert, Richard G.; Durham, Sean; Burts, Diane C. – Early Education and Development, 2018
Research Findings: This study builds on prior work related to the assessment of young dual language learners (DLLs). The purposes of the study were to (a) determine whether latent subgroups of preschool DLLs would replicate those found previously and (b) examine the validity of GOLDĀ® by Teaching Strategies with empirically derived subgroups.…
Descriptors: Preschool Education, Teaching Methods, Bilingualism, Bilingual Education
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Qian, Xiaoyu; Nandakumar, Ratna; Glutting, Joseoph; Ford, Danielle; Fifield, Steve – ETS Research Report Series, 2017
In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…
Descriptors: Item Analysis, Gender Differences, Achievement Gap, Grade 8
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Zwick, Rebecca – ETS Research Report Series, 2012
Differential item functioning (DIF) analysis is a key component in the evaluation of the fairness and validity of educational tests. The goal of this project was to review the status of ETS DIF analysis procedures, focusing on three aspects: (a) the nature and stringency of the statistical rules used to flag items, (b) the minimum sample size…
Descriptors: Test Bias, Sample Size, Bayesian Statistics, Evaluation Methods
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Wang, Xiaohui; Bradlow, Eric T.; Wainer, Howard; Muller, Eric S. – Journal of Educational and Behavioral Statistics, 2008
In the course of screening a form of a medical licensing exam for items that function differentially (DIF) between men and women, the authors used the traditional Mantel-Haenszel (MH) statistic for initial screening and a Bayesian method for deeper analysis. For very easy items, the MH statistic unexpectedly often found DIF where there was none.…
Descriptors: Bayesian Statistics, Licensing Examinations (Professions), Medicine, Test Items
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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
Sympson, James B. – 1976
Latent trait test score theory is discussed primarily in terms of Birnbaum's three-parameter logistic model, and with some reference to the Rasch model. Equations and graphic illustrations are given for item characteristic curves and item information curves. An example is given for a hypothetical 20-item adaptive test, showing cumulative results…
Descriptors: Adaptive Testing, Bayesian Statistics, Item Analysis, Latent Trait Theory
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
Wilcox, Rand – 1977
False-positive and false-negative dicisions are the fundamental errors committed with a mastery test; yet the estimation of the likelihood of committing these errors has not been investigated. Accordingly, two methods of estimating the likelihood of committing these errors are described and then investigated using Monte Carlo techniques.…
Descriptors: Bayesian Statistics, Computer Programs, Error Patterns, Item Analysis
Sinharay, Sandip; Almond, Russell; Yan, Duanli – Educational Testing Service, 2004
Model checking is a crucial part of any statistical analysis. As educators tie models for testing to cognitive theory of the domains, there is a natural tendency to represent participant proficiencies with latent variables representing the presence or absence of the knowledge, skills, and proficiencies to be tested (Mislevy, Almond, Yan, &…
Descriptors: Statistical Analysis, Epistemology, Educational Assessment, Item Response Theory
Clark, Cynthia L., Ed. – 1976
The principal objectives of this conference were to exchange information, discuss theoretical and empirical developments, and to coordinate research efforts. The papers and their authors are: "The Graded Response Model of Latent Trait Theory and Tailored Testing" by Fumiko Samejima; (Incomplete Orders and Computerized Testing" by…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Branching
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