University of Milano-Bicocca, Monza, Italy.
School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Neurol Sci. 2022 Feb;43(2):961-966. doi: 10.1007/s10072-021-05374-0. Epub 2021 Jun 17.
Norming neuropsychological tests and standardizing their raw scores are needed to draw objective clinical judgments on clients' neuropsychological profile. The Equivalent Score (ES) method is a regression-based normative/standardization technique that relies on the non-parametric identification of the observations corresponding to the outer and inner tolerance limits (oTL; iTL) - to derive a cut-off, as well as to between-ES thresholds - to mark the passage across different levels of ability. However, identifying these observations is still a time-consuming, "manual" procedure. This work aimed at providing practitioners with a user-friendly code that helps compute TLs and ES thresholds.
R language and RStudio environment were adopted. A function for identifying the observations corresponding to both TLs by exploiting Beta distribution features was implemented. A code for identifying the observations corresponding to ES thresholds according to a z-deviate-based approach is also provided.
An exhaustive paradigm of usage of both the aforementioned function and script has been carried out. A user-friendly, online applet is provided for the calculation of both TLs and ESs thresholds. A brief summary of the regression-based procedure preceding the identification of TLs and ESs threshold is also given (along with an R script implementing these steps).
The present work provides with a software solution to the calculation of TLs and ES thresholds for norming/standardizing neuropsychological tests. These software can help reduce both the subjectivity and the error rate when applying the ES method, as well as simplify and expedite its implementation.
为了对客户的神经心理学状况进行客观的临床判断,需要对神经心理学测试进行标准化并将其原始分数规范化。等效分数(ES)方法是一种基于回归的规范/标准化技术,它依赖于对外限(oTL)和内限(iTL)的非参数识别-得出一个截止值,以及在 ES 之间的阈值-以标记不同能力水平之间的过渡。然而,识别这些观察值仍然是一个耗时的“手动”过程。这项工作旨在为从业者提供一个用户友好的代码,帮助计算 TL 和 ES 阈值。
采用了 R 语言和 RStudio 环境。实现了一种通过利用 Beta 分布特征来识别与两个 TL 对应的观察值的函数。还提供了一种根据 z-偏离基方法识别与 ES 阈值对应的观察值的代码。
对上述功能和脚本的使用进行了详尽的范例。还提供了一个用于计算 TL 和 ES 阈值的用户友好的在线小程序。还简要总结了在识别 TL 和 ES 阈值之前基于回归的过程(以及一个实现这些步骤的 R 脚本)。
本工作为神经心理学测试的规范/标准化计算 TL 和 ES 阈值提供了一个软件解决方案。这些软件可以帮助减少应用 ES 方法时的主观性和错误率,并简化和加快其实施。