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Rosso, Martin A.; Reckase, Mark D. – 1981
The overall purpose of this research was to compare a maximum likelihood based tailored testing procedure to a Bayesian tailored testing procedure. The results indicated that both tailored testing procedures produced equally reliable ability estimates. Also an analysis of test length indicated that reasonable ability estimates could be obtained…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing
Shermis, Mark D.; And Others – 1992
The reliability of four branching algorithms commonly used in computer adaptive testing (CAT) was examined. These algorithms were: (1) maximum likelihood (MLE); (2) Bayesian; (3) modal Bayesian; and (4) crossover. Sixty-eight undergraduate college students were randomly assigned to one of the four conditions using the HyperCard-based CAT program,…
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Comparative Analysis
McKinley, Robert L.; Reckase, Mark D. – 1981
A study was conducted to compare tailored testing procedures based on a Bayesian ability estimation technique and on a maximum likelihood ability estimation technique. The Bayesian tailored testing procedure selected items so as to minimize the posterior variance of the ability estimate distribution, while the maximum likelihood tailored testing…
Descriptors: Academic Ability, Adaptive Testing, Bayesian Statistics, Comparative Analysis
Spray, Judith A.; Reckase, Mark D. – 1994
The issue of test-item selection in support of decision making in adaptive testing is considered. The number of items needed to make a decision is compared for two approaches: selecting items from an item pool that are most informative at the decision point or selecting items that are most informative at the examinee's ability level. The first…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing