Discussion on the ranking method for standardized residency training assessment based on an improved algorithm of confidence intervals
Gong Bin
Wang Zhengyang
Abstract：Objective To solve the issue that existing ranking algorithms based on the absolute value of the standardized residency training examination pass rate overlooked the statistical uncertainty.Methods To enhance the accuracy and reliability of the assessment,a ranking method improved with confidence intervals was employed.Results Analysis of sample data demonstrated that the improved algorithm,which took into account of both the absolute value of the examination pass rate and the size of each training base,effectively resolved the assessment bias caused by statistical uncertainty in the original ranking.Conclusion The improved algorithm has significant advantages in evaluating the credibility of the examination pass rates,identifying potential outstanding training bases,and reducing misjudgment of assessment due to small sample sizes.It provides a valuable reference for decision-makers.
Keywords：rankingsmall samplesuncertaintyconfidence intervalsstandardized residency training
Publication Date：2024-10-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 797-800 )