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Applied Psychological Measurement, 2005
The Rasch testlet model for both dichotomous and polytomous items in testlet-based tests is proposed. It can be viewed as a special case of the multidimensional random coefficients multinomial logit model (MRCMLM). Therefore, the estimation procedures for the MRCMLM can be directly applied. Simulations were conducted to examine parameter recovery under
Mark Wilson, Wen Chung Wang
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The Rasch testlet model for both dichotomous and polytomous items in testlet-based tests is proposed. It can be viewed as a special case of the multidimensional random coefficients multinomial logit model (MRCMLM). Therefore, the estimation procedures for the MRCMLM can be directly applied. Simulations were conducted to examine parameter recovery under
Mark Wilson, Wen Chung Wang
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Validation of Science Achievement Test with the Rasch Model
, 2016The purpose of this study was to validate the test items of science achievement, which were used as a test at Pancasakti Science Competition, in order to obtain enough valid test items with the Rasch model application.
P. Susongko
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2019
A category coefficient \( \kappa_{k} \) is the sum of the exceeded thresholds for response category k. The PRM can be rewritten in terms of principal components (Guttman) for the thresholds instead of the thresholds themselves. The principal component \( \lambda \) characterizes the spread of the responses, the principal component \( \eta ...
David Andrich, Ida Marais
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A category coefficient \( \kappa_{k} \) is the sum of the exceeded thresholds for response category k. The PRM can be rewritten in terms of principal components (Guttman) for the thresholds instead of the thresholds themselves. The principal component \( \lambda \) characterizes the spread of the responses, the principal component \( \eta ...
David Andrich, Ida Marais
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A Dynamic Generalization of the Rasch Model
Psychometrika, 1993In the present paper a model for describing dynamic processes is constructed by combining the common Rasch model with the concept of structurally incomplete designs. This is accomplished by mapping each item on a collection of virtual items, one of which is assumed to be presented to the respondent dependent on the preceding responses and/or the ...
N.D. Verhelst, Cornelis A.W. Glas
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1995
In this chapter, it is shown that the problem of evaluating model fit can be solved within the framework of the general multinomial model, and it is shown how tests for this framework can be adapted to the Rasch model. Four types of tests are considered: generalized Pearson tests, likelihood ratio tests, Wald tests, and likelihood ratio tests.
Cees A. W. Glas, Norman D. Verhelst
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In this chapter, it is shown that the problem of evaluating model fit can be solved within the framework of the general multinomial model, and it is shown how tests for this framework can be adapted to the Rasch model. Four types of tests are considered: generalized Pearson tests, likelihood ratio tests, Wald tests, and likelihood ratio tests.
Cees A. W. Glas, Norman D. Verhelst
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Conditions for Rasch-Dichotomizability of the Unidimensional Polytomous Rasch Model
Psychometrika, 1989Jansen and Roskam (1986) discussed the compatibility of the unidimensional polytomous Rasch model with dichotomization of the response continuum. They derived a rather strict condition in which dichotomization of multicategory data that fit the unidimensional polytomous Rasch model, results in dichotomous data which fit the dichotomous Research model ...
Paul Jansen, Edward E. Roskam
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2007
Over the past few years, several studies have investigated and demonstrated the relationships between generalized linear mixed models (GLIMM) and item response modeling. Some benefits associated with this GLIMM-based modeling framework include the modeling of nested structure of data, such as examinees nested within schools (Kamata, 2001), of ...
Akihito Kamata, Yuk Fai Cheong
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Over the past few years, several studies have investigated and demonstrated the relationships between generalized linear mixed models (GLIMM) and item response modeling. Some benefits associated with this GLIMM-based modeling framework include the modeling of nested structure of data, such as examinees nested within schools (Kamata, 2001), of ...
Akihito Kamata, Yuk Fai Cheong
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A New Derivation of the Rasch Model
1984Abstract The Rasch model is usually derived from statistical requirements of estimation of its parameters. The principle of 'specific objectivity' or, equivalently, 'sample independence' requires that subject parameters can be estimated independent from the item parameters and vice versa. This in turn requires that sufficient statistics exist for the
Edw.E. Roskam, Paul Jansen
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Modeling Local Item Dependence Due to Common Test Format With a Multidimensional Rasch Model
, 2015Research shows that test method can exert a significant impact on test takers’ performance and thereby contaminate test scores. We argue that common test method can exert the same effect as common stimuli and violate the conditional independence ...
Purya Baghaei, Vahid Aryadoust
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MISUNDERSTANDING THE RASCH MODEL
Journal of Educational Measurement, 1977Whitely and Dawis (1974) recently discussed, in this journal, the nature of objectivity with the Rasch model. They made several good points. However, their paper contained some unfortunate misunderstandings and errors. One important misunderstanding concerns the estimation procedure necessary to calibrate items according to the Rasch model. The authors
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