The most probable distribution method is applied to derive the logistic model as the distribution accounting for the maximum number of possible outcomes in a dichotomous test while introducing latent traits and item characteristics as constraints to the system. The item response theory logistic models, with a particular focus on the one-parameter logistic model, or Rasch model, and their properties and assumptions, are discussed for both infinite and finite populations
Rasch model item parameters can be estimated consistently with a pseudo-likelihood method based on...
For item responses fitting the Rasch model, the assumptions under-lying the Mokken model of double m...
A structural model of the ability distribution in the item response theory is proposed in which cont...
The most probable distribution method is applied to derive the logistic model as the distribution ac...
Boltzmann's most probable distribution method is applied to derive the Polytomous Rasch model as the...
Item response theory models arose from the inherent limitations of classical test theory methods of ...
The Item Response Theory represents a group of statistical models and tests which might be used for ...
Among the varieties of logistic models, those at-tributed to Birnbaum (involving the parameters of i...
Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a lo...
In their seminal work on characterizing the manifest probabilities of latent trait models, Cressie a...
Analyzing latent variables is becoming more and more important in several fields, such as clinical r...
Fisher's information measure for the item difficulty parameter in the Rasch model and its marginal a...
Rasch model item parameters can be estimated consistently with a pseudo-likelihood method based on c...
For analyzing item response data, item response theory (IRT) models treat the discrete responses to ...
The large samples and item pools required for accurate parameter estimation under the three-paramete...
Rasch model item parameters can be estimated consistently with a pseudo-likelihood method based on...
For item responses fitting the Rasch model, the assumptions under-lying the Mokken model of double m...
A structural model of the ability distribution in the item response theory is proposed in which cont...
The most probable distribution method is applied to derive the logistic model as the distribution ac...
Boltzmann's most probable distribution method is applied to derive the Polytomous Rasch model as the...
Item response theory models arose from the inherent limitations of classical test theory methods of ...
The Item Response Theory represents a group of statistical models and tests which might be used for ...
Among the varieties of logistic models, those at-tributed to Birnbaum (involving the parameters of i...
Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a lo...
In their seminal work on characterizing the manifest probabilities of latent trait models, Cressie a...
Analyzing latent variables is becoming more and more important in several fields, such as clinical r...
Fisher's information measure for the item difficulty parameter in the Rasch model and its marginal a...
Rasch model item parameters can be estimated consistently with a pseudo-likelihood method based on c...
For analyzing item response data, item response theory (IRT) models treat the discrete responses to ...
The large samples and item pools required for accurate parameter estimation under the three-paramete...
Rasch model item parameters can be estimated consistently with a pseudo-likelihood method based on...
For item responses fitting the Rasch model, the assumptions under-lying the Mokken model of double m...
A structural model of the ability distribution in the item response theory is proposed in which cont...