Multivariate Modeling of Student Performance on NBME Subject Exams

Aim This study sought to determine whether it was possible to develop statistical models which could be used to accurately correlate student performance on clinical subject exams based on their National Board of Medical Examiner (NBME) self-assessment performance and other variables, described below, as such tools are not currently available. Methods Students at a large public medical school were provided fee vouchers for NBME self-assessments before clinical subject exams. Multivariate regression models were then developed based on how self-assessment performance correlated to student success on the subsequent subject exam (Medicine, Surgery, Family Medicine, Obstetrics-Gynecology, Pediatrics, and Psychiatry) while controlling for the proximity of the self-assessment to the exam, USMLE Step 1 score, and the academic quarter. Results The variables analyzed satisfied the requirements of linear regression. The correlation strength of individual variables and overall models varied by discipline and outcome (equated percent correct or percentile, Model R Range: 0.1799-0.4915). All models showed statistical significance on the Omnibus F-test (p