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Li, Jun Corser; Woodruff, David J. – 2002
Coefficient alpha is a simple and very useful index of test reliability that is widely used in educational and psychological measurement. Classical statistical inference for coefficient alpha is well developed. This paper presents two methods for Bayesian statistical inference for a single sample alpha coefficient. An approximate analytic method…
Descriptors: Bayesian Statistics, Markov Processes, Monte Carlo Methods, Reliability
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Jones, W. Paul; Newman, F. L. – Educational and Psychological Measurement, 1971
Descriptors: Bayesian Statistics, Decision Making, Hypothesis Testing, Performance Criteria
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Vijn, Pieter; Molenaar, Ivo W. – Journal of Educational Statistics, 1981
In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)
Descriptors: Aptitude Treatment Interaction, Bayesian Statistics, Mastery Tests, Mathematical Models
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Zwick, Rebecca; Thayer, Dorothy T. – Applied Psychological Measurement, 2002
Used a simulation to investigate the applicability to computerized adaptive test data of a differential item functioning (DIF) analysis method. Results show the performance of this empirical Bayes enhancement of the Mantel Haenszel DIF analysis method to be quite promising. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Item Bias
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Mislevy, Robert J. – Applied Psychological Measurement, 1988
A framework is described for exploiting auxiliary information about test items within item response theory models to enhance parameter estimates. The method also provides diagnostic information about items' operating characteristics. An empirical Bayesian estimation of Rasch item difficulty is used to illustrate the principles involved. (TJH)
Descriptors: Bayesian Statistics, Difficulty Level, Equations (Mathematics), Estimation (Mathematics)
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Games, Paul A. – Journal of Experimental Education, 1988
A distinction is made between statistics based on scientific theory and theory-free statistics. This distinction is discussed in the contexts of hypothesis testing, Bayesian inference, a priori planned contrasts, a new simple computational method, and alternative data interpretations. (TJH)
Descriptors: Bayesian Statistics, Computation, Hypothesis Testing, Scientific Research
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Bradlow, Eric T.; Wainer, Howard; Wang, Xiaohui – Psychometrika, 1999
Proposes a parametric approach that involves a modification of standard Item Response Theory models that explicitly accounts for the nesting of items within the same testlets and that can be applied to multiple-choice sections comprising a mixture of independent items and testlets. (Author/SLD)
Descriptors: Bayesian Statistics, Item Response Theory, Models, Multiple Choice Tests
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Bajari, Patrick; Hortacsu, Ali – Journal of Political Economy, 2005
Recently, economists have developed methods for structural estimation of auction models. Many researchers object to these methods because they find the strict rationality assumptions to be implausible. Using bid data from first-price auction experiments, we estimate four alternative structural models: (1) risk-neutral Bayes-Nash, (2) risk-averse…
Descriptors: Computation, Bids, Models, Bayesian Statistics
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Stanfield, William D.; Carlton, Matthew A. – American Biology Teacher, 2004
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
Descriptors: Probability, Bayesian Statistics, Computation, Biology
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Khuri, Andre – International Journal of Mathematical Education in Science and Technology, 2004
The Dirac delta function has been used successfully in mathematical physics for many years. The purpose of this article is to bring attention to several useful applications of this function in mathematical statistics. Some of these applications include a unified representation of the distribution of a function (or functions) of one or several…
Descriptors: Maximum Likelihood Statistics, Bayesian Statistics, Statistics, College Mathematics
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Goenner, Cullen F.; Snaith, Sean M. – Research in Higher Education, 2004
Empirical analysis requires researchers to choose which variables to use as controls in their models. Theory should dictate this choice, yet often in social science there are several theories that may suggest the inclusion or exclusion of certain variables as controls. The result of this is that researchers may use different variables in their…
Descriptors: Models, Prediction, Graduation Rate, Universities
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Trafimow, David – Psychological Review, 2005
In their comment on D. Trafimow, M. D. Lee and E. Wagenmakers argued that the requisite probabilities to use in Bayes's theorem can always be found. In the present reply, the author asserts that M. D. Lee and E. Wagenmakers use a problematic assumption and that finding the requisite probabilities is not straightforward. After describing the…
Descriptors: Probability, Bayesian Statistics, Error Patterns, Criticism
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Sinharay, Sandip – Journal of Educational Measurement, 2005
Even though Bayesian estimation has recently become quite popular in item response theory (IRT), there is a lack of works on model checking from a Bayesian perspective. This paper applies the posterior predictive model checking (PPMC) method (Guttman, 1967; Rubin, 1984), a popular Bayesian model checking tool, to a number of real applications of…
Descriptors: Measurement Techniques, Item Response Theory, Bayesian Statistics, Models
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Zhu, Mu; Lu, Arthur Y. – Journal of Statistics Education, 2004
In Bayesian statistics, the choice of the prior distribution is often controversial. Different rules for selecting priors have been suggested in the literature, which, sometimes, produce priors that are difficult for the students to understand intuitively. In this article, we use a simple heuristic to illustrate to the students the rather…
Descriptors: Bayesian Statistics, Maximum Likelihood Statistics, Probability, Statistical Distributions
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Linn, Shai – Journal of Statistics Education, 2004
Courses in clinical epidemiology usually include acquainting students with a single 2X2 table. All diagnostic test characteristics are explained using this table. This pedagogic approach may be misleading. A new didactic approach is hereby proposed, using two tables, each with specific analogous notations (uppercase and lowercase) and derived…
Descriptors: Epidemiology, Diagnostic Tests, Bayesian Statistics, Prediction
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