Selecting a measurement model for the analysis of the National Institutes of Health Stroke Scale.
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.
Iramaneerat
Cherdsak
C
Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkoknoi, Bangkok10700, Thailand. iramanec@hotmail.com
Smith
Everett V
EV
Millis
Scott R
SR
Lyden
Patrick D
PD
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001925:Brain Damage, Chronic / Q000209:etiology; D002545:Brain Ischemia / Q000150:complications; D002544:Cerebral Infarction / Q000150:complications / Q000473:pathology; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D012189:Retrospective Studies; D012720:Severity of Illness Index; D020521:Stroke / Q000145:classification* / Q000150:complications; D055815:Young Adult