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Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
Chang, Hua-Hua; Stout, William – 1991
The empirical Bayes modeling approach--latent ability random sampling in the item response theory (IRT) context--to the IRT modeling of psychological tests is described. Under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test.…
Descriptors: Ability, Bayesian Statistics, Equations (Mathematics), Item Response Theory
Peer reviewedViana, Marlos A. G. – Journal of Educational Statistics, 1993
Use of linear combinations of Fisher's "z" transformations as a combined test for the common correlation parameter based on "k" independent sample correlations has been previously studied. This article considers additional "z" additive properties and methods of combining independent studies when planning the number of…
Descriptors: Bayesian Statistics, Correlation, Equations (Mathematics), Evaluation Criteria
Kuo, Lynn; Cohen, Michael P. – 1993
Bayesian methods for estimating dose response curves in quantal bioassay are studied. A linearized multi-stage model is assumed for the shape of the curves. A Gibbs sampling approach with data augmentation is employed to compute the Bayes estimates. In addition, estimation of the "relative additional risk" and the "risk specific…
Descriptors: Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics), Mathematical Models
PDF pending restorationMeyer, Donald L. – 1971
Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent…
Descriptors: Bayesian Statistics, Data Analysis, Decision Making, Mathematical Models
Larsson, B. – 1972
An experimental study of the efficiency of human information processing is based on the Bayesian model for simple hypothesis testing with fixed binomial sampling. Each of 60 subjects is analyzed with separate ANOVAs focusing on two efficiency variables. Sample size and critical value are also analyzed. Subjects show very different utilization of…
Descriptors: Bayesian Statistics, Cognitive Processes, Hypothesis Testing, Information Processing
Peer reviewedNovick, Melvin R.; And Others – Psychometrika, 1973
This paper develops theory and methods for the application of the Bayesian Model II method to the estimation of binomial proportions and demonstrates its application to educational data. (Author/RK)
Descriptors: Bayesian Statistics, Educational Testing, Mathematical Models, Measurement
Miller, John K.; Knapp, Thomas R.
The testing of research hypotheses is directly comparable to the dichotomous decision-making of medical diagnosis or jury trials--not ill/ill, or innocent/guilty decisions. There are costs in both kinds of error, type I errors of falsely rejecting a null hypothesis or type II errors of falsely rejecting an alternative hypothesis. It is important…
Descriptors: Bayesian Statistics, Decision Making, Educational Research, Hypothesis Testing
Peer reviewedLin, Miao-Hsiang; Hsiung, Chao A. – Psychometrika, 1992
Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)
Descriptors: Bayesian Statistics, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Lord, Frederic M. – 1971
A numerical procedure is outlined for obtaining an interval estimate of a parameter in an empirical Bayes estimation problem. The case where each observed value x has a binomial distribution, conditional on a parameter zeta, is the only case considered. For each x, the parameter estimated is the expected value of zeta given x. The main purpose is…
Descriptors: Bayesian Statistics, Computer Programs, Expectation, Goodness of Fit
Peer reviewedAlbert, James H. – Journal of Educational Statistics, 1992
Estimating item parameters from a two-parameter normal ogive model is considered using Gibbs sampling to simulate draws from the joint posterior distribution of ability and item parameters. The method gives marginal posterior density estimates for any parameter of interest, as illustrated using data from a 33-item mathematics placement…
Descriptors: Algorithms, Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics)
Fyans, Leslie J., Jr. – 1978
Unlike the past models guiding cross-cultural psychological research, a new paradigm facilitates multiple level investigations by incorporating both culture-specific (nested) and culture-general (crossed) independent variables within its partially-hierarchical framework. Based upon the generalizability analysis, this model generates sequential…
Descriptors: Analysis of Variance, Bayesian Statistics, Cognitive Processes, Comparative Analysis

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