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Robertson, S. E.; Teather, D. – Journal of Documentation, 1974
A model is proposed to explain the retrieval characteristics of an information retrieval system. (Author)
Descriptors: Bayesian Statistics, Information Retrieval, Information Systems, Mathematical Models

Meyer, Donald L. – American Educational Research Journal, 1974
See TM 501 202-3 and EJ 060 883 for related articles. (MLP)
Descriptors: Bayesian Statistics, Hypothesis Testing, Power (Statistics), Research Design

Vale, C. David; Weiss, David J. – 1977
An alternative item-selection procedure for use with Owen's Bayesian adaptive testing strategy is proposed. This procedure is, by design, faster than Owen's original procedure because it searches only part of the total item pool. Item selections are, however, identical for both methods. After a conceptual development of the rapid-search procedure,…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Programs, Item Banks
Ferguson, Richard L; Novich, Melvin R. – 1973
The decision process required for Individually Prescribed Instruction (IPI), an adaptive instructional program developed at the University of Pittsburgh, is described. In IPI, short tests are used to determine the level of proficiency of each student in precisely defined learning objectives. The output of these tests is used to guide instructional…
Descriptors: Bayesian Statistics, Computer Assisted Instruction, Decision Making, Individualized Instruction
Diamond, James – 1964
The use of Bayesian statistics as the basis of classical analysis of data is described. Bayesian analysis is a set of procedures for changing opinions about a given phenomenon based upon rational observation of a set of data. The Bayesian arrives at a set of prior beliefs regarding some states of nature; he observes data in a study and then…
Descriptors: Bayesian Statistics, Educational Research, Newsletters, Prediction
Brumet, Michael E. – 1976
Bayesian statistical inference is unfamiliar to many educational evaluators. While the classical model is useful in educational research, it is not as useful in evaluation because of the need to identify solutions to practical problems based on a wide spectrum of information. The reason Bayesian analysis is effective for decision making is that it…
Descriptors: Bayesian Statistics, Decision Making, Educational Research, Evaluation

Duff, William L., Jr.; Lynch, Robert M. – Journal of Experimental Education, 1977
In this study, the graduate school admission policy at a medium-sized, state-supported university is analyzed using a combination of Bayesian and cost/benefit decision analysis techniques. (Author)
Descriptors: Admission Criteria, Bayesian Statistics, Decision Making, Graduate Study
Campbell, Janell; Campbell, Richard – Health Education (Washington D.C.), 1987
Mandatory drug testing of workers will create problems due to the low predictive ability of urinalysis. The predictive value of drug testing in populations of low drug incidence is illustrated using Bayes' Theorem. (MT)
Descriptors: Bayesian Statistics, Employment Practices, Illegal Drug Use, Screening Tests

Duthie, Bruce; Vincent, Ken R. – Journal of Clinical Psychology, 1986
Diagnostic hit rates for the Diagnostic Inventory of Personality and Symptoms were compared to diagnosis by psychiatrists of the same patients. The Probability Scale employing Bayesian concepts and base rates correctly classified 70% of the patients and was more accurate by far than the other two methods used. (Author/ABB)
Descriptors: Bayesian Statistics, Identification, Personality Measures, Psychological Testing
Interval Estimation for True Scores under Various Scale Transformations. ACT Research Report Series.
Lee, Won-Chan; Brennan, Robert L.; Kolen, Michael J. – 2002
This paper reviews various procedures for constructing an interval for an individual's true score given the assumption that errors of measurement are distributed as binomial. This paper also presents two general interval estimation procedures (i.e., normal approximation and endpoints conversion methods) for an individual's true scale score;…
Descriptors: Bayesian Statistics, Error of Measurement, Estimation (Mathematics), Scaling
Li, Jun Corser; Woodruff, David J. – 2002
Coefficient alpha is a simple and very useful index of test reliability that is widely used in educational and psychological measurement. Classical statistical inference for coefficient alpha is well developed. This paper presents two methods for Bayesian statistical inference for a single sample alpha coefficient. An approximate analytic method…
Descriptors: Bayesian Statistics, Markov Processes, Monte Carlo Methods, Reliability

Jones, W. Paul; Newman, F. L. – Educational and Psychological Measurement, 1971
Descriptors: Bayesian Statistics, Decision Making, Hypothesis Testing, Performance Criteria

Vijn, Pieter; Molenaar, Ivo W. – Journal of Educational Statistics, 1981
In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)
Descriptors: Aptitude Treatment Interaction, Bayesian Statistics, Mastery Tests, Mathematical Models

Zwick, Rebecca; Thayer, Dorothy T. – Applied Psychological Measurement, 2002
Used a simulation to investigate the applicability to computerized adaptive test data of a differential item functioning (DIF) analysis method. Results show the performance of this empirical Bayes enhancement of the Mantel Haenszel DIF analysis method to be quite promising. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Item Bias

Mislevy, Robert J. – Applied Psychological Measurement, 1988
A framework is described for exploiting auxiliary information about test items within item response theory models to enhance parameter estimates. The method also provides diagnostic information about items' operating characteristics. An empirical Bayesian estimation of Rasch item difficulty is used to illustrate the principles involved. (TJH)
Descriptors: Bayesian Statistics, Difficulty Level, Equations (Mathematics), Estimation (Mathematics)