A Class of Multidimensional Latent Class IRT Models for Ordinal Polytomous Item Responses

@article{Bacci2012ACO,
  title={A Class of Multidimensional Latent Class IRT Models for Ordinal Polytomous Item Responses},
  author={Silvia Bacci and Francesco Bartolucci and Michela Gnaldi},
  journal={Communications in Statistics - Theory and Methods},
  year={2012},
  volume={43},
  pages={787 - 800}
}
We propose a class of multidimensional Item Response Theory models for polytomously-scored items with ordinal response categories. This class extends an existing class of multidimensional models for dichotomously-scored items in which the latent abilities are represented by a random vector assumed to have a discrete distribution, with support points corresponding to different latent classes in the population. In the proposed approach, we allow for different parameterizations for the conditional… 

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References

SHOWING 1-10 OF 61 REFERENCES

Linear Logistic Latent Class Analysis for Polytomous Data

Abstract For latent class analysis, a widely known statistical method for the unmixing of an observed frequency table into several unobservable ones, a flexible model is presented in order to

A logistic mixture distribution model for polychotomous item responses

The polychotomous Rasch model is generalized to a mixture distribution model. It is assumed that the observed data are generated by two or more latent classes of individuals so that within each class

A comparison of latent trait and latent class analyses of Likert-type data

This paper brings together and compares two developments in the analysis of Likert attitude scales. The first is the generalization of latent class models to ordered response categories. The second

Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis

Abstract The Rasch model for item analysis is an important member of the class of exponential response models in which the number of nuisance parameters increases with the number of subjects, leading

A rasch model for partial credit scoring

A unidimensional latent trait model for responses scored in two or more ordered categories is developed. This “Partial Credit” model is a member of the family of latent trait models which share the

Fitting a Polytomous Item Response Model to Likert-Type Data

This study examined the application of the MML-EM algorithm to the parameter estimation problems of the normal ogive and logistic polytomous response models for Likert-type items. A rating-scale

A multidimensional item response model: Constrained latent class analysis using the gibbs sampler and posterior predictive checks

It is shown that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models and the Gibbs sampler is an excellent tool if inequality constraints have to be taken into consideration when making inferences.

Testing unidimensionality in polytomous Rasch models

A fundamental assumption of most IRT models is that items measure the same unidimensional latent construct. For the polytomous Rasch model two ways of testing this assumption against specific

COMPARISON OF MULTIDIMENSIONAL ITEM RESPONSE MODELS: MULTIVARIATE NORMAL ABILITY DISTRIBUTIONS VERSUS MULTIVARIATE POLYTOMOUS ABILITY DISTRIBUTIONS

Multidimensional item response models can be based on multivariate normal ability distributions or on multivariate polytomous ability distributions. For the case of simple structure in which each
...