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- W2282882364 abstract "A model for simultaneous optimization of combinations of test-based decisions in education and psychology is proposed using Bayesian decision theory. To illustrate the approach, one classification decision with two treatments each followed by a mastery decision are combined into a decision network. An important decision is made between weak and strong decision rules. As opposed to strong rules, weak rules are allowed to be a function of prior test scores in the series. Conditions under which optimal rules take weak monotone forms are derived. Results from a well-known problem in The Netherlands of selecting optimal continuation schools on the basis of achievement test scores are presented.KeywordsBayesian Decision TheoryClassification DecisionsMastery TestingSimultaneous OptimizationCompensatory Rules" @default.
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- W2282882364 date "1998-01-01" @default.
- W2282882364 modified "2023-09-27" @default.
- W2282882364 title "Compensatory Rules for Optimal Classification with Mastery Scores" @default.
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- W2282882364 doi "https://doi.org/10.1007/978-3-642-72253-0_29" @default.
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