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小规模客观结构化临床考试中的标准设定:改良临界组法与临界回归法的比较

Standard setting in a small scale OSCE: a comparison of the Modified Borderline-Group Method and the Borderline Regression Method.

作者信息

Wood Timothy J, Humphrey-Murto Susan M, Norman Geoffrey R

机构信息

Medical Council of Canada and Faculty of Medicine, University of Ottawa, K1G-3H7, ON, Ottawa, Canada.

出版信息

Adv Health Sci Educ Theory Pract. 2006 May;11(2):115-22. doi: 10.1007/s10459-005-7853-1.

Abstract

When setting standards, administrators of small-scale OSCEs often face several challenges, including a lack of resources, a lack of available expertise in statistics, and difficulty in recruiting judges. The Modified Borderline-Group Method is a standard setting procedure that compensates for these challenges by using physician examiners and is easy to use making it a good choice for small scale OSCEs. Unfortunately, the use of this approach may introduce a new challenge. Because a small scale OSCE has a small number of examinees, there may be few examinees in the borderline range, which could introduce an unintentional bias. A standard setting method called The Borderline Regression Method will be described. This standard setting method is similar to the Modified Borderline-Group Method but incorporates a linear regression approach allowing the cut score to be set using the scores from all examinees and not from a subset. The current study uses confidence intervals to analyze the precision of cut scores derived from both approaches when applied to a small scale OSCE.

摘要

在制定标准时,小型客观结构化临床考试(OSCE)的管理人员常常面临若干挑战,包括资源匮乏、缺乏统计学方面的可用专业知识以及招募考官困难。改良临界组法是一种标准设定程序,通过使用医师考官来应对这些挑战,并且易于使用,这使其成为小型OSCE的一个不错选择。不幸的是,使用这种方法可能会带来一个新的挑战。由于小型OSCE的考生数量较少,处于临界分数区间的考生可能很少,这可能会引入无意的偏差。将介绍一种名为临界回归法的标准设定方法。这种标准设定方法与改良临界组法类似,但采用了线性回归方法,允许使用所有考生的分数而非子集的分数来设定及格分数。本研究使用置信区间来分析这两种方法应用于小型OSCE时得出的及格分数的精度。

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