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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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Hendrawan, Irene; Glas, Cees A. W.; Meijer, Rob R. – Applied Psychological Measurement, 2005
The effect of person misfit to an item response theory model on a mastery/nonmastery decision was investigated. Furthermore, it was investigated whether the classification precision can be improved by identifying misfitting respondents using person-fit statistics. A simulation study was conducted to investigate the probability of a correct…
Descriptors: Probability, Statistics, Test Length, Simulation
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Regier, Terry; Gahl, Susanne – Cognition, 2004
Syntactic knowledge is widely held to be partially innate, rather than learned. In a classic example, it is sometimes argued that children know the proper use of anaphoric "one," although that knowledge could not have been learned from experience. Lidz et al. [Lidz, J., Waxman, S., & Freedman, J. (2003). What infants know about syntax but couldn't…
Descriptors: Learning Processes, Syntax, Language Acquisition, Cognitive Development
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de la Torre, Jimmy; Patz, Richard J. – Journal of Educational and Behavioral Statistics, 2005
This article proposes a practical method that capitalizes on the availability of information from multiple tests measuring correlated abilities given in a single test administration. By simultaneously estimating different abilities with the use of a hierarchical Bayesian framework, more precise estimates for each ability dimension are obtained.…
Descriptors: Scoring, Markov Processes, Item Response Theory, Tests
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Stern, Hal S. – Psychological Methods, 2005
I. Klugkist, O. Laudy, and H. Hoijtink (2005) presented a Bayesian approach to analysis of variance models with inequality constraints. Constraints may play 2 distinct roles in data analysis. They may represent prior information that allows more precise inferences regarding parameter values, or they may describe a theory to be judged against the…
Descriptors: Probability, Inferences, Bayesian Statistics, Data Analysis
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Wang, Wen-Chung; Chen, Po-Hsi – Applied Psychological Measurement, 2004
Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random…
Descriptors: Item Analysis, Adaptive Testing, Computer Assisted Testing, Computer Simulation
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Meyer, Katrina A.; Xu, Yonghong Jade – Internet and Higher Education, 2007
This study answered questions about which faculty come to use technology in their teaching and used a novel statistical analysis to develop a model that captures the primary factors influencing faculty technology use. It used a sample of 16,914 faculty within the 2004 National Study of Postsecondary Faculty to explore explanations for faculty…
Descriptors: Classification, Educational Technology, Bayesian Statistics, College Faculty
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Lockwood, J. R.; McCaffrey, Daniel F.; Mariano, Louis T.; Setodji, Claude – Journal of Educational and Behavioral Statistics, 2007
There is increased interest in value-added models relying on longitudinal student-level test score data to isolate teachers' contributions to student achievement. The complex linkage of students to teachers as students progress through grades poses both substantive and computational challenges. This article introduces a multivariate Bayesian…
Descriptors: Urban Schools, Academic Persistence, Reading Achievement, Mathematics Achievement
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Almond, Russell G.; Mulder, Joris; Hemat, Lisa A.; Yan, Duanli – ETS Research Report Series, 2006
Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task that may be dependent. This paper explores four design patterns for modeling locally dependent observations from the same task: (1) No context--Ignore dependence among observables; (2) Compensatory…
Descriptors: Bayesian Statistics, Networks, Models, Design
Mislevy, Robert J.; Huang, Chun-Wei – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
Advances in cognitive research increase the need for assessment that can address the processes and the strategies by which persons solve problems. Several psychometric models have been introduced to handle claims cast in information-processing terms, explicitly modeling performance in terms of theory-based predictions of performance. Cognitively…
Descriptors: Cognitive Science, Cognitive Processes, Problem Solving, Psychometrics
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Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego – Journal of Educational Measurement, 2007
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Descriptors: Inferences, Models, Item Response Theory, Cognitive Measurement
Mislevy, Robert J. – 1993
Relationships between Bayesian ability estimates and the parameters of a normal population distribution are derived in the context of classical test theory. Analogies are provided for use as approximations in work with item response theory (IRT). The following issues are addressed: (1) the relationship between the distribution of the latent…
Descriptors: Ability, Bayesian Statistics, Computer Software, Estimation (Mathematics)
Mislevy, Robert J. – 1994
Recent developments in cognitive psychology suggest models for knowledge and learning that often fall outside the realm of standard test theory. This paper concerns probability-based inference in terms of such models. The essential idea is to define a space of "student models"--simplified characterizations of students' knowledge, skill,…
Descriptors: Bayesian Statistics, Cognitive Processes, Cognitive Psychology, Educational Diagnosis
Wang, Jianjun – 1995
Effects of blind guessing on the success of passing true-false and multiple-choice tests are investigated under a stochastic binomial model. Critical values of guessing are thresholds which signify when the effect of guessing is negligible. By checking a table of critical values assembled in this paper, one can make a decision with 95% confidence…
Descriptors: Bayesian Statistics, Grading, Guessing (Tests), Models
Mislevy, Robert J. – 1988
When using item response theory (IRT) models in educational and psychological measurement, it is standard practice to estimate the operating characteristics of test items from examinees' item responses alone. This is the final report of a project that employed Bayesian and empirical Bayesian methods to exploit additional information that is often…
Descriptors: Bayesian Statistics, Cognitive Processes, Educational Assessment, Estimation (Mathematics)
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