Jamovi Optimal cut-off points, ROC Curve, AUC & Diagnostic Test Accuracy

In this tutorial, we will demonstrate how to choose Optimal cut-off points for a diagnostic test with their specificity, senstivity, PPV, NPP; to design ROC (Receiver Operator Characteristic) graphs and AUC (the area under the curve) easily using jamovi software.
DeLong's test can be used to show if the AUCs of two models are statistically significantly different.
The "dichotomized 6-month GOS score" was considered as the main outcome variable [reference], with ranges 1-2-3 and 4-5 reflecting unfavorable and favorable (Good) outcome, respectively.
The aim is to determine accuracy of WFNS (World Federation of Neurosurgical Societies) grading system at admission and serum markers ( S100β, NDKA ) as possible predictors.
Special thanks to Jamovi and PPDA developpers.

[@kaoutaranouartadlaoui5187]

We could understand better with a voice explication. Thank you

[@sallesbarbosah]

Thanks

[@drabdurrahman19]

Dataset used in this tutorial: Subarachnoid hemorrhage data (search.r-project.org/CRAN/refmans/pROC/html/aSAH.html )