A rasch model for partial credit scoring |
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Authors: | Geoff N Masters |
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Institution: | (1) Department of Education, University of Chicago, 5835 S. Kimbark, 60637 Chicago |
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Abstract: | 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 property of parameter separability and so permit “specifically
objective” comparisons of persons and items. The model can be viewed as an extension of Andrich's Rating Scale model to situations
in which ordered response alternatives are free to vary in number and structure from item to item. The difference between
the parameters in this model and the “category boundaries” in Samejima's Graded Response model is demonstrated. An unconditional
maximum likelihood procedure for estimating the model parameters is developed.
Preparation of this paper was supported by grants from the Spencer Foundation and the National Institute for Justice. I would
like to thank Professor Benjamin D. Wright of the University of Chicago for his very kind help with the various drafts of
this paper. |
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Keywords: | latent trait Rasch model ordered categories partial credit |
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