Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
The prediction models for the United States Medical Licensure
Examination (USMLE) Steps 1 and 2 performances were
constructed by the Monte Carlo simulation modeling approach
via linear regression. The purpose of this study was to build the
robust simulation models to accurately identify the most
important predictors and yield the valid range estimations of the
Steps 1 and 2 scores. The application of simulation modeling
approach was deemed an effective way in predicting student
performances on licensure examinations. Also, sensitivity
analysis (a/k/a what-if analysis) in the simulation models was
used to predict the magnitudes of Steps 1 and 2 affected by
changes in the National Board of Medical Examiners (NBME)
Basic Science Subject Board scores. In addition, the study
results indicated that the Medical College Admission Test
(MCAT) Verbal Reasoning score and Step 1 score were
significant predictors of the Step 2 performance. Hence,
institutions could screen qualified student applicants for
interviews and document the effectiveness of basic science
education program based on the simulation results.
