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Using Markov chain model to evaluate medical students’ trajectory on progress tests and predict USMLE step 1 scores---a retrospective cohort study in one medical school by Wang, Ling (author);Laird-Fick, Heather S. (author);Parker, Carol J. (author);Solomon, David (author) is a Medicine article available to read on EtoBox.

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## Background Medical students must meet curricular expectations and pass national licensing examinations to become physicians. However, no previous studies explicitly modeled stages of medical students acquiring basic science knowledge. In this study, we employed an innovative statistical model to characterize students’ growth using progress testing results over time and predict licensing examination performance. ## Methods All students matriculated from 2016 to 2017 in our medical school with USMLE Step 1 test scores were included in this retrospective cohort study (__N__ = 358). Markov chain method was employed to: 1) identify latent states of acquiring scientific knowledge based on progress tests and 2) estimate students’ transition probabilities between states. The primary outcome of this study, United States Medical Licensing Examination (USMLE) Step 1 performance, were predicted based on students’ estimated probabilities in each latent state identified by Markov chain model. ## Results Four latent states were identified based on students’ progress test results: Novice, Advanced Beginner I, Advanced Beginner II and Competent States. At the end of the first year, students pred

Who reads Using Markov chain model to evaluate medical students’ trajectory on progress tests and predict USMLE step 1 scores---a retrospective cohort study in one medical school?

Author

Wang, Ling (author);Laird-Fick, Heather S. (author);Parker, Carol J. (author);Solomon, David (author)

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Medicine (Health Sciences)