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Peer reviewedHarwell, Michael R.; Janosky, Janine E. – Applied Psychological Measurement, 1991
Investigates the BILOG computer program's ability to recover known item parameters for different numbers of items, examinees, and variances of the prior distributions of discrimination parameters for the two-parameter logistic item-response theory model. For samples of at least 250 examinees and 15 items, simulation results support using BILOG.…
Descriptors: Bayesian Statistics, Computer Simulation, Estimation (Mathematics), Item Response Theory
Peer reviewedKim, Seock-Ho; And Others – Psychometrika, 1994
Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item and ability parameters through two joint and two marginal Bayesian procedures. Marginal procedures yielded smaller root mean square differences for item and ability, but results for larger sample size and test length were similar.…
Descriptors: Ability, Bayesian Statistics, Computer Simulation, Estimation (Mathematics)
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)
Peer reviewedDe Ayala, R. J.; And Others – Journal of Educational Measurement, 1990
F. M. Lord's flexilevel, computerized adaptive testing (CAT) procedure was compared to an item-response theory-based CAT procedure that uses Bayesian ability estimation with various standard errors of estimates used for terminating the test. Ability estimates of flexilevel CATs were as accurate as were those of Bayesian CATs. (TJH)
Descriptors: Ability Identification, Adaptive Testing, Bayesian Statistics, Comparative Analysis
Peer reviewedGifford, Janice A.; Swaminathan, Hariharan – Applied Psychological Measurement, 1990
The effects of priors and amount of bias in the Bayesian approach to the estimation problem in item response models are examined using simulation studies. Different specifications of prior information have only modest effects on Bayesian estimates, which are less biased than joint maximum likelihood estimates for small samples. (TJH)
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Simulation, Estimation (Mathematics)
Peer reviewedDe Ayala, R. J. – Educational and Psychological Measurement, 1992
Effects of dimensionality on ability estimation of an adaptive test were examined using generated data in Bayesian computerized adaptive testing (CAT) simulations. Generally, increasing interdimensional difficulty association produced a slight decrease in test length and an increase in accuracy of ability estimation as assessed by root mean square…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Rule, David L. – 1993
Several regression methods were examined within the framework of weighted structural regression (WSR), comparing their regression weight stability and score estimation accuracy in the presence of outlier contamination. The methods compared are: (1) ordinary least squares; (2) WSR ridge regression; (3) minimum risk regression; (4) minimum risk 2;…
Descriptors: Analysis of Covariance, Bayesian Statistics, Comparative Analysis, Computer Simulation
Vale, C. David; Gialluca, Kathleen A. – 1985
ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Kirisci, Levent; Hsu, Tse-Chi – 1992
A predictive adaptive testing (PAT) strategy was developed based on statistical predictive analysis, and its feasibility was studied by comparing PAT performance to those of the Flexilevel, Bayesian modal, and expected a posteriori (EAP) strategies in a simulated environment. The proposed adaptive test is based on the idea of using item difficulty…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing


