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An Introduction to Item Response Theory and Rasch Analysis: Application Using the Eating Assessment Tool (EAT-10)

Published online by Cambridge University Press:  07 December 2017

Jacob Kean Open the ORCID record for Jacob Kean [Opens in a new window] ,
Erica F. Bisson ,
Darrel S. Brodke ,
Joshua Biber  and
Paul H. Gross
Jacob Kean*
Affiliation:
Population Health Sciences, University of Utah School of Medicine, Utah, USA
Erica F. Bisson
Affiliation:
Department of Neurosurgery, University of Utah School of Medicine, Utah, USA
Darrel S. Brodke
Affiliation:
Department of Orthopedics, University of Utah School of Medicine, Utah, USA
Joshua Biber
Affiliation:
Population Health Sciences, University of Utah School of Medicine, Utah, USA
Paul H. Gross
Affiliation:
Population Health Sciences, University of Utah School of Medicine, Utah, USA
*
Address for correspondence: Jacob Kean, Population Health Sciences, University of Utah School of Medicine, 295 Chipeta Way, Rm 1N455, Salt Lake City, Utah, USA. E-mail: jacob.kean@hsc.utah.edu
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Abstract

Item response theory has its origins in educational measurement and is now commonly applied in health-related measurement of latent traits, such as function and symptoms. This application is due, in large part, to gains in the precision of measurement attributable to item response theory and corresponding decreases in response burden, study costs, and study duration. The purpose of this paper is twofold: introduce basic concepts of item response theory and demonstrate this analytic approach in a worked example, a Rasch model (1PL) analysis of the Eating Assessment Tool (EAT-10), a commonly used measure for oropharyngeal dysphagia. The results of the analysis were largely concordant with previous studies of the EAT-10 and illustrate for brain impairment clinicians and researchers how IRT analysis can yield greater precision of measurement.

Keywords

Deglutition DisordersCervical VertebraeNeurosurgical ProceduresPsychometrics
Type
Articles
Information
Brain Impairment , Volume 19 , Special Issue 1: Quantitative Data Analysis; by Robyn Tate and Michael Perdices , March 2018 , pp. 91 - 102
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2017 

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