The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential mastery test, the decision is to classify a subject as a master or a nonmaster, or to continue sampling and administering another random test item. The framework of minimax sequential decision theory (minimum information approach) is used; that is, optimal rules are obtained by minimizing the maximum expected losses associated with all possible decision rules at each stage of sampling. The binomial model is assumed for the probability of a correct response given the true level of functioning, whereas threshold loss is adopted for the loss function involved. Monotonicity conditions are derived, that is, conditions sufficient for optimal rules t...
The purpose of this paper is to formulate decision rules for adapting the appropriate amount of inst...
A classical problem in mastery testing is the choice of passing score and test length so that the ma...
The purpose of this paper is to formulate optimal sequential decision rules for adapting the appropr...
This paper derives optimal rules for sequential mastery tests. In a sequential mastery test, the dec...
The purpose of this paper is to derive optimal rules for variable-length mastery tests in case three...
The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential m...
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework ...
A classical problem in mastery testing is the choice of passing score and test length so that the ma...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-b...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
A theoretical framework for mastery testing based on item response theory and Bayesian decision th...
The purpose of this paper is to formulate decision rules for adapting the appropriate amount of inst...
A classical problem in mastery testing is the choice of passing score and test length so that the ma...
The purpose of this paper is to formulate optimal sequential decision rules for adapting the appropr...
This paper derives optimal rules for sequential mastery tests. In a sequential mastery test, the dec...
The purpose of this paper is to derive optimal rules for variable-length mastery tests in case three...
The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential m...
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework ...
A classical problem in mastery testing is the choice of passing score and test length so that the ma...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-b...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
A theoretical framework for mastery testing based on item response theory and Bayesian decision th...
The purpose of this paper is to formulate decision rules for adapting the appropriate amount of inst...
A classical problem in mastery testing is the choice of passing score and test length so that the ma...
The purpose of this paper is to formulate optimal sequential decision rules for adapting the appropr...