Norms and standardizations in neuropsychology via equivalent scores: software solutions and practical guides

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Abstract

Background: 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. Methods: 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. Results: 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). Discussion: 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.

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APA

Aiello, E. N., & Depaoli, E. G. (2022). Norms and standardizations in neuropsychology via equivalent scores: software solutions and practical guides. Neurological Sciences, 43(2), 961–966. https://doi.org/10.1007/s10072-021-05374-0

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