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Peer reviewedSwaminathan, Hariharan; Hambleton, Ronald K.; Sireci, Stephen G.; Xing, Dehui; Rizavi, Saba M. – Applied Psychological Measurement, 2003
Descriptors: Bayesian Statistics, Estimation (Mathematics), Item Response Theory, Sample Size
Peer reviewedSong, Xin-Yuan; Lee, Sik-Yum – Structural Equation Modeling, 2002
Developed a Bayesian approach for a general multigroup nonlinear factor analysis model that simultaneously obtains joint Bayesian estimates of the factor scores and the structural parameters subjected to some constraints across different groups. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Factor Analysis, Scores
Peer reviewedLaird, Nan M.; Louis, Thomas A. – Journal of Educational Statistics, 1989
Based on the Gaussian model, methods for using measurements that depend on the true attribute to compute rankings are proposed and compared. Measurements based on an empirical Bayes model produce estimates that differ from ranking observed data. Ranking methods are illustrated with school achievement data. (TJH)
Descriptors: Bayesian Statistics, Class Rank, Mathematical Formulas, Mathematical Models
Peer reviewedOaksford, Mike; Chater, Nick – Psychological Review, 1994
Experimental data on human reasoning in hypothesis-testing tasks is reassessed in light of a Bayesian model of optimal data selection in inductive hypothesis testing. The rational analysis provided by the model suggests that reasoning in such tasks may be rational rather than subject to systematic bias. (SLD)
Descriptors: Bayesian Statistics, Hypothesis Testing, Induction, Models
Peer reviewedLenk, Peter J.; DeSarbo, Wayne S. – Psychometrika, 2000
Presents a hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The approach combines the flexibility of semiparametric latent class models that assume common parameters for each subpopulation and the parsimony of random effects models that assume normal distributions for the regression parameters.…
Descriptors: Bayesian Statistics, Monte Carlo Methods, Simulation, Statistical Distributions
Peer reviewedSeltzer, Michael H.; And Others – Journal of Educational and Behavioral Statistics, 1996
The Gibbs sampling algorithms presented by M. H. Seltzer (1993) are fully generalized to a broad range of settings in which vectors of random regression parameters in the hierarchical model are assumed multivariate normally or multivariate "t" distributed across groups. The use of a fully Bayesian approach is discussed. (SLD)
Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Multivariate Analysis
Griffiths, Thomas L.; Tenenbaum, Joshua B. – Cognitive Psychology, 2005
We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…
Descriptors: Probability, Logical Thinking, Inferences, Causal Models
Guarino, Cassandar; Ridgeway, Greg; Chun, Marc; Buddin, Richard – Higher Education in Europe, 2005
This study applies a Bayesian latent variable analysis to the task of determining rankings of universities in the UK and US, on the basis of a set of quality-related measures. It estimates the degree of uncertainty in the rankings and permits the assessment of statistically significant differences across universities. It also provides a…
Descriptors: Evaluation Methods, Evaluation Criteria, Bayesian Statistics, Higher Education
Weitzman, R. A. – Journal of Educational and Behavioral Statistics, 2006
Focusing on a single sample obtained randomly with replacement from a single population, this article examines the regression of population on sample proportions and develops an unbiased estimator of the square of the correlation between them. This estimator turns out to be the regression coefficient. Use of the squared-correlation estimator as a…
Descriptors: Sample Size, Intervals, Credibility, Computation
Nelson, Jonathan D. – Psychological Review, 2005
Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment,…
Descriptors: Probability, Norms, Bayesian Statistics, Statistical Analysis
Rakow, Tim; Newell, Ben R.; Fayers, Kathryn; Hersby, Mette – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2005
The authors identify and provide an integration of 3 criteria for establishing cue-search hierarchies in inferential judgment. Cues can be ranked by information value according to expected information gain (Bayesian criterion), cue-outcome correlation (correlational criterion), or ecological validity (accuracy criterion). All criteria…
Descriptors: Cues, Inferences, Criteria, Bayesian Statistics
Kern, John C. – Journal of Statistics Education, 2006
Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…
Descriptors: Bayesian Statistics, Probability, Inferences, Statistics
Zhang, Junni L.; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2003
The topic of "truncation by death" in randomized experiments arises in many fields, such as medicine, economics and education. Traditional approaches addressing this issue ignore the fact that the outcome after the truncation is neither "censored" nor "missing," but should be treated as being defined on an extended sample space. Using an…
Descriptors: Experiments, Predictor Variables, Bayesian Statistics, Death
Ogletree, August E. – ProQuest LLC, 2009
Two needs of Georgia State University Professional Development School Partnerships are to show increases in both student academic achievement and teacher efficacy. The Teacher-Intern-Professor (TIP) Model was designed to address these needs. The TIP model focuses on using the university and school partnership to support Georgia State University…
Descriptors: Control Groups, Quasiexperimental Design, Professional Development Schools, Teacher Effectiveness
Garcia, Patricio; Amandi, Analia; Schiaffino, Silvia; Campo, Marcelo – Computers & Education, 2007
Students are characterized by different learning styles, focusing on different types of information and processing this information in different ways. One of the desirable characteristics of a Web-based education system is that all the students can learn despite their different learning styles. To achieve this goal we have to detect how students…
Descriptors: Student Behavior, Internet, Web Based Instruction, Artificial Intelligence

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