Cherdsak IramaneeratEverett V. SmithScott R. MillisPatrick D. LydenMahidol UniversityUniversity of Illinois at ChicagoWayne State UniversityUniversity of California, San Diego, School of Medicine2018-09-132018-09-132009-11-04International Journal of Neuroscience. Vol.119, No.7 (2009), 1042-105915635279002074542-s2.0-68149158500https://repository.li.mahidol.ac.th/handle/20.500.14594/28299To 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.Mahidol UniversityNeuroscienceArticleSCOPUS10.1080/00207450801909100