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| Bayesian Statistics | 7 |
| Mathematical Models | 7 |
| Scoring | 7 |
| Adaptive Testing | 5 |
| Simulation | 4 |
| Computer Oriented Programs | 3 |
| Item Analysis | 3 |
| Response Style (Tests) | 3 |
| Test Construction | 3 |
| Branching | 2 |
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Author
| Chernyshenko, Oleksandr S. | 1 |
| Drasgow, Fritz | 1 |
| Hsu, Tse-Chi | 1 |
| Huynh, Huynh | 1 |
| Kirisci, Levent | 1 |
| Segall, Daniel O. | 1 |
| Stark, Stephen | 1 |
| Weiss, David J. | 1 |
| Weiss, David J., Ed. | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Evaluative | 3 |
| Reports - Research | 2 |
| Speeches/Meeting Papers | 2 |
| Collected Works - Proceedings | 1 |
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Peer reviewedHuynh, Huynh – Journal of Educational and Behavioral Statistics, 1998
Presents a procedure, based on a Bayesian updating of the item information, for locating on the latent trait scale the scores or responses of items that follow the three-parameter logistic and monotone partial credit models. Applications are provided in terms of selecting items or score categories for criterion-referenced interpretation of mapping…
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Item Analysis, Likert Scales
Stark, Stephen; Chernyshenko, Oleksandr S.; Drasgow, Fritz – Applied Psychological Measurement, 2005
This article proposes an item response theory (IRT) approach to constructing and scoring multidimensional pairwise preference items. Individual statements are administered and calibrated using a unidimensional single-stimulus model. Tests are created by combining multidimensional items with a small number of unidimensional pairings needed to…
Descriptors: Test Construction, Scoring, Mathematical Models, Item Response Theory
Peer reviewedSegall, Daniel O. – Psychometrika, 1996
Maximum likelihood and Bayesian procedures are presented for item selection and scoring of multidimensional adaptive tests. A demonstration with simulated response data illustrates that multidimensional adaptive testing can provide equal or higher reliabilities with fewer items than are required in one-dimensional adaptive testing. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Equations (Mathematics)
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
PDF pending restorationCivil Service Commission, Washington, DC. Personnel Research and Development Center. – 1976
This pamphlet reprints three papers and an invited discussion of them, read at a Division 5 Symposium at the 1975 American Psychological Association Convention. The first paper describes a Bayesian tailored testing process and shows how it demonstrates the importance of using test items with high discrimination, low guessing probability, and a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Oriented Programs, Computer Programs
Weiss, David J. – 1976
Three and one-half years of research on computerized ability testing are summarized. The original objectives of the research were: (1) to develop and implement the stratified computer-based ability test; (2) to compare, on psychometric criteria, the various approaches to computer-based ability testing, including the stratified computerized test,…
Descriptors: Adaptive Testing, Bayesian Statistics, Branching, Comparative Analysis
Weiss, David J., Ed. – 1977
This symposium consists of five papers and presents some recent developments in adaptive testing which have applications to several military testing problems. The overview, by James R. McBride, defines adaptive testing and discusses some of its item selection and scoring strategies. Item response theory, or item characteristic curve theory, is…
Descriptors: Ability, Achievement Tests, Adaptive Testing, Bayesian Statistics

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