An approach to simultaneous optimization of assignments of subjects to treatments followed by an end-of-mastery test is presented using the framework of Bayesian decision theory. Focus is on demonstrating how rules for the simultaneous optimization of sequences of decisions can be found. The main advantages of the simultaneous approach, compared to the separate approach, are the more efficient use of data and the fact that more realistic utility structures can be used. The utility structure dealt with it this combined decision problem is a linear utility function. Decision rules are derived for quota-free as well as quota-restricted assignment situations when several culturally biased subpopulations of subjects are to be distinguished. The ...
For assigning subjects to treatments the point of intersection of within-group regression lines is o...
For assigning subjects to treatments he point of intersection of within-group regression lines is or...
A theoretical framework for mastery testing based on item response theory and Bayesian decision th...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
The purpose of this paper is to simultaneously optimize decision rules for combinations of elementar...
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-b...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework ...
The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential m...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The classification problem consists of assigning subjects to one of several available treatments on ...
The purpose of this paper is to formulate optimal sequential decision rules for adapting the appropr...
This paper reviews recent research in the Netherlands on the application of decision theory to test-...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
For assigning subjects to treatments the point of intersection of within-group regression lines is o...
For assigning subjects to treatments he point of intersection of within-group regression lines is or...
A theoretical framework for mastery testing based on item response theory and Bayesian decision th...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
The purpose of this paper is to simultaneously optimize decision rules for combinations of elementar...
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-b...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework ...
The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential m...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The classification problem consists of assigning subjects to one of several available treatments on ...
The purpose of this paper is to formulate optimal sequential decision rules for adapting the appropr...
This paper reviews recent research in the Netherlands on the application of decision theory to test-...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
For assigning subjects to treatments the point of intersection of within-group regression lines is o...
For assigning subjects to treatments he point of intersection of within-group regression lines is or...
A theoretical framework for mastery testing based on item response theory and Bayesian decision th...