Equating With Polytomous Item Response Models

2015 ◽  
Author(s):  
Seonghoon Kim ◽  
Deborah J. Harris ◽  
Michael J. Kolen
Keyword(s):  
Item Response ◽  
Response Models ◽  
Item Response Models ◽  
Polytomous Item ◽  
Polytomous Item Response

Using Polytomous Item Response Models to Assess Death Anxiety

2007 ◽  
Vol 56 (2) ◽  
pp. 89-96 ◽  
Author(s):  
Juana G??mez ◽  
M. Dolores Hidalgo ◽  
Joaqu??n Tom??s-S??bado
Keyword(s):  
Item Response ◽  
Death Anxiety ◽  
Response Models ◽  
Item Response Models ◽  
Polytomous Item ◽  
Polytomous Item Response

Comparison of Dichotomous and Polytomous Item Response Models in Equating Scores from Tests Composed of Testlets

2001 ◽  
Vol 25 (4) ◽  
pp. 357-372 ◽  
Author(s):  
Guemin Lee ◽  
Michael J. Kolen ◽  
David A. Frisbie ◽  
Robert D. Ankenmann
Keyword(s):  
Item Response ◽  
Response Models ◽  
Item Response Models ◽  
Polytomous Item ◽  
Polytomous Item Response

scholarly journals Scale Alignment in the Between-Item Multidimensional Partial Credit Model

2021 ◽  
pp. 014662162110131
Author(s):  
Leah Feuerstahler ◽  
Mark Wilson
Keyword(s):  
Item Response ◽  
Kindergarten Readiness ◽  
Latent Trait ◽  
Individual Development ◽  
Partial Credit Model ◽  
Partial Credit ◽  
Response Models ◽  
Item Response Models ◽  
Item Parameters ◽  
Polytomous Item Response

In between-item multidimensional item response models, it is often desirable to compare individual latent trait estimates across dimensions. These comparisons are only justified if the model dimensions are scaled relative to each other. Traditionally, this scaling is done using approaches such as standardization—fixing the latent mean and standard deviation to 0 and 1 for all dimensions. However, approaches such as standardization do not guarantee that Rasch model properties hold across dimensions. Specifically, for between-item multidimensional Rasch family models, the unique ordering of items holds within dimensions, but not across dimensions. Previously, Feuerstahler and Wilson described the concept of scale alignment, which aims to enforce the unique ordering of items across dimensions by linearly transforming item parameters within dimensions. In this article, we extend the concept of scale alignment to the between-item multidimensional partial credit model and to models fit using incomplete data. We illustrate this method in the context of the Kindergarten Individual Development Survey (KIDS), a multidimensional survey of kindergarten readiness used in the state of Illinois. We also present simulation results that demonstrate the effectiveness of scale alignment in the context of polytomous item response models and missing data.

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