NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 1 to 15 of 23 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Adrian Quintero; Emmanuel Lesaffre; Geert Verbeke – Journal of Educational and Behavioral Statistics, 2024
Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Sampling
Peer reviewed Peer reviewed
Direct linkDirect link
van der Linden, Wim J.; Ren, Hao – Journal of Educational and Behavioral Statistics, 2020
The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee's ability and optimally…
Descriptors: Bayesian Statistics, Adaptive Testing, Error of Measurement, Markov Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Vidotto, Davide; Vermunt, Jeroen K.; van Deun, Katrijn – Journal of Educational and Behavioral Statistics, 2018
With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…
Descriptors: Bayesian Statistics, Multivariate Analysis, Data, Hierarchical Linear Modeling
Peer reviewed Peer reviewed
Direct linkDirect link
Slater, Stefan; Joksimovic, Srecko; Kovanovic, Vitomir; Baker, Ryan S.; Gasevic, Dragan – Journal of Educational and Behavioral Statistics, 2017
In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…
Descriptors: Data Analysis, Data Processing, Computer Uses in Education, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Guarino, Cassandra M.; Maxfield, Michelle; Reckase, Mark D.; Thompson, Paul N.; Wooldridge, Jeffrey M. – Journal of Educational and Behavioral Statistics, 2015
Empirical Bayes's (EB) estimation has become a popular procedure used to calculate teacher value added, often as a way to make imprecise estimates more reliable. In this article, we review the theory of EB estimation and use simulated and real student achievement data to study the ability of EB estimators to properly rank teachers. We compare the…
Descriptors: Bayesian Statistics, Computation, Teacher Evaluation, Teacher Effectiveness
Peer reviewed Peer reviewed
Direct linkDirect link
Merkle, Edgar C. – Journal of Educational and Behavioral Statistics, 2011
Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…
Descriptors: Statistical Analysis, Factor Analysis, Bayesian Statistics, Comparative Analysis
Peer reviewed Peer reviewed
Kasim, Rafa M.; Raudenbush, Stephen W. – Journal of Educational and Behavioral Statistics, 1998
Gibbs sampling was applied to obtain Bayes inferences in the case of unbalanced multilevel data when the homogeneity of variance assumption fails and when interest focuses on inferences for some or all of the groups' variances. This approach is compared to a more standard analysis based on restricted maximum-likelihood statistics. (SLD)
Descriptors: Bayesian Statistics, Statistical Inference
Peer reviewed Peer reviewed
Gross, Alan L. – Journal of Educational and Behavioral Statistics, 1997
An analytic expression is derived for the posterior distribution of the bivariate correlation given a data set that contains missing values on both variables. Interval estimates of the unknown correlation are then computed in terms of the highest posterior density regions. A sampling study illustrates the procedure. (SLD)
Descriptors: Bayesian Statistics, Correlation, Estimation (Mathematics)
Peer reviewed Peer reviewed
Lecoutre, Bruno; Charron, Camilo – Journal of Educational and Behavioral Statistics, 2000
Illustrates procedures for prediction analysis in 2 X 2 contingency tables through the analyses of solutions of six types of problems associated with the acquisition of fractions. Reviews and extends confidence interval procedures previously proposed for an index of predictive efficiency of implication hypotheses. Compares frequentist coverage…
Descriptors: Bayesian Statistics, Hypothesis Testing, Prediction, Probability
Peer reviewed Peer reviewed
Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven; Gelman, Andrew; Maris, Eric – Journal of Educational and Behavioral Statistics, 2001
Presents a fully Bayesian analysis for the Probability Matrix Decomposition (PMD) model using the Gibbs sampler. Identifies the advantages of this approach and illustrates the approach by applying the PMD model to opinions of respondents from different countries concerning the possibility of contracting AIDS in a specific situation. (SLD)
Descriptors: Bayesian Statistics, Matrices, Probability, Psychometrics
Peer reviewed Peer reviewed
Zwick, Rebecca; Thayer, Dorothy; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2000
Studied a method for flagging differential item functioning (DIF) based on loss functions. Builds on earlier research that led to the development of an empirical Bayes enhancement to the Mantel-Haenszel DIF analysis. Tested the method through simulation and found its performance better than some commonly used DIF classification systems. (SLD)
Descriptors: Bayesian Statistics, Identification, Item Bias, Simulation
Peer reviewed Peer reviewed
Direct linkDirect link
Edwards, Michael C.; Vevea, Jack L. – Journal of Educational and Behavioral Statistics, 2006
This article examines a subscore augmentation procedure. The approach uses empirical Bayes adjustments and is intended to improve the overall accuracy of measurement when information is scant. Simulations examined the impact of the method on subscale scores in a variety of realistic conditions. The authors focused on two popular scoring methods:…
Descriptors: Geometric Concepts, True Scores, Scoring, Item Response Theory
Peer reviewed Peer reviewed
Boik, Robert J. – Journal of Educational and Behavioral Statistics, 1997
An analysis of repeated measures designs is proposed that uses an empirical Bayes estimator of the covariance matrix. The proposed analysis behaves like a univariate analysis when sample size is small or sphericity nearly satisfied, but behaves like multivariate analysis when sample size is large or sphericity is strongly violated. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Multivariate Analysis, Research Design
Peer reviewed Peer reviewed
Seltzer, 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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Previous Page | Next Page ยป
Pages: 1  |  2