The classification problem consists of assigning subjects to one of several available treatments on the basis of their test scores, where the success of each treatment is measured by a different criterion. It is indicated how this problem can be formulated as an (empirical) Bayes decision problem. As an example, the case of classification with a threshold utility function is analyzed, and optimal assignment rules are derived. The results are illustrated empirically with data from a classification problem in which achievement test data are used to assign students to appropriate continuation schools. The classification problem consists of assigning subjects to one of several available treatments on the basis of their test scores, where the su...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The goal of this study was to develop four statistical models and to apply Bayesian decision theory ...
The classification problem consists of assigning subjects to one of several available treatments on ...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
For assigning subjects to treatments the point of intersection of within-group regression lines is o...
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...
This paper reviews recent research in the Netherlands on the application of decision theory to test-...
For assigning subjects to treatments he point of intersection of within-group regression lines is or...
We address the problem of selecting the best of a set of units based on a criterion variable, when i...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A model for simultaneous optimization of combinations of test-based decisions in psychology and educ...
The purpose of this paper is to simultaneously optimize decision rules for combinations of elementar...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The goal of this study was to develop four statistical models and to apply Bayesian decision theory ...
The classification problem consists of assigning subjects to one of several available treatments on ...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Fo...
For assigning subjects to treatments the point of intersection of within-group regression lines is o...
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...
This paper reviews recent research in the Netherlands on the application of decision theory to test-...
For assigning subjects to treatments he point of intersection of within-group regression lines is or...
We address the problem of selecting the best of a set of units based on a criterion variable, when i...
An approach to simultaneous optimization of assignments of subjects to treatments followed by an end...
A model for simultaneous optimization of combinations of test-based decisions in psychology and educ...
The purpose of this paper is to simultaneously optimize decision rules for combinations of elementar...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simulta...
The goal of this study was to develop four statistical models and to apply Bayesian decision theory ...