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A sequential cognitive diagnosis model for graded response
2017Cognitive diagnosis models (CDMs) have received increasing attention in recent years. The goal of CDMs is to classify examinees into different latent classes with unique attribute patterns indicating mastery or nonmastery on a set of skills or attributes of interest.
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Multidimensional Grade Response Model
Acta Psychologica Sinica, 2013Wen-Jiu DU, Han-Min XIAO
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Generalized fiducial inference for graded response models
2015Generalized fiducial inference (GFI) has been proposed as an alternative inferential framework in the statistical literature. Inferences of various sorts, such as confidence regions for (possibly transformed) model parameters, making prediction about future observations, and goodness of fit evaluation, can be constructed from a fiducial distribution ...
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Psychometrika, 2008
Samejima (Psychometrika 65:319–335, 2000) proposed the logistic positive exponent family of models (LPEF) for dichotomous responses in the unidimensional latent space. The objective of the present paper is to propose and discuss a graded response model that is expanded from the LPEF, in the context of item response theory (IRT).
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Samejima (Psychometrika 65:319–335, 2000) proposed the logistic positive exponent family of models (LPEF) for dichotomous responses in the unidimensional latent space. The objective of the present paper is to propose and discuss a graded response model that is expanded from the LPEF, in the context of item response theory (IRT).
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Some Standard Errors of the Graded Response Model
Proceedings of the 90th Annual International Meeting of the Psychometric SocietyA procedure to calculate the asymptotic standard errors of the estimated parameters of the graded response model in the logistic form is described. The asymptotic standard errors computed from the sampling variances of maximum likelihood estimates are tabulated for some common situations.
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Performance of the S −χ 2 Statistic for the Multidimensional Graded Response Model
Educational and Psychological Measurement, 2021Shiyang Su, Chun Wang
exaly