Publication: Selecting a measurement model for the analysis of the national institutes of health stroke scale
Issued Date
2009-11-04
Resource Type
ISSN
15635279
00207454
00207454
Other identifier(s)
2-s2.0-68149158500
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Neuroscience. Vol.119, No.7 (2009), 1042-1059
Suggested Citation
Cherdsak Iramaneerat, Everett V. Smith, Scott R. Millis, Patrick D. Lyden Selecting a measurement model for the analysis of the national institutes of health stroke scale. International Journal of Neuroscience. Vol.119, No.7 (2009), 1042-1059. doi:10.1080/00207450801909100 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/28299
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Title
Selecting a measurement model for the analysis of the national institutes of health stroke scale
Abstract
To select the most appropriate model for the analysis of data from the National Institutes of Health Stroke Scale (NIHSS), the graded-response, Rasch partial credit, and generalized partial credit models were used to analyze NIH stroke data of 1,191 acute ischemic stroke patients. Based on Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC), the generalized partial credit model has the most generalizable parameters. Items on the NIHSS have different discriminating powers. The generalized partial credit model, which allows varying slopes of item response functions, is the most appropriate model for the analysis of the NIHSS.