Jørgensen Morten, Konge Lars, Subhi Yousif
1Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
2Copenhagen Academy for Medical Education and Simulation, Capital Region of Denmark, Copenhagen, Denmark.
Adv Simul (Lond). 2018 Mar 9;3:5. doi: 10.1186/s41077-018-0064-7. eCollection 2018.
The contrasting groups' standard setting method is commonly used for consequences analysis in validity studies for performance in medicine and surgery. The method identifies a pass/fail cut-off score, from which it is possible to determine false positives and false negatives based on observed numbers in each group. Since groups in validity studies are often small, e.g., due to a limited number of experts, these analyses are sensitive to outliers on the normal distribution curve.
We propose that these shortcomings can be addressed in a simple manner using the cumulative distribution function.
We demonstrate considerable absolute differences between the observed false positives/negatives and the theoretical false positives/negatives. In addition, several important examples are given.
We propose that a better reporting strategy is to report theoretical false positives and false negatives together with the observed false positives and negatives, and we have developed an Excel sheet to facilitate such calculations.
Not relevant.
在医学和外科手术操作有效性研究的结果分析中,对比组标准设定方法被广泛应用。该方法确定一个通过/未通过的临界分数,据此可以根据每组观察到的数量确定假阳性和假阴性。由于有效性研究中的组通常较小,例如由于专家数量有限,这些分析对正态分布曲线上的异常值很敏感。
我们提出,可以用累积分布函数以一种简单的方式解决这些缺点。
我们证明了观察到的假阳性/阴性与理论上的假阳性/阴性之间存在相当大的绝对差异。此外,还给出了几个重要的例子。
我们建议更好的报告策略是同时报告理论上的假阳性和假阴性以及观察到的假阳性和阴性,并且我们开发了一个Excel工作表来方便此类计算。
不相关。