EvalTest: A 'shiny' App to Evaluate Diagnostic Tests Performance
Evaluate diagnostic test performance using data from laboratory or diagnostic research. It supports both binary and continuous test variables. It allows users to compute key performance indicators and visualize Receiver Operating Characteristic (ROC) curves, determine optimal cut-off thresholds, display confusion matrix, and export publication-ready plot. It aims to facilitate the application of statistical methods in diagnostic test evaluation by healthcare professionals. The methodology used to compute the performance indicators follows the overview described by Habibzadeh (2025) <doi:10.11613/BM.2025.010101>. Thanks to 'shiny' package.
| Version: |
1.0.2 |
| Depends: |
R (≥ 4.2.1) |
| Imports: |
DT, ggplot2, ggpubr, openxlsx, pROC, readxl, shiny, shinydashboard, stats, binom |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2025-09-14 |
| Author: |
Nassim AYAD  [aut,
cre] (affiliation: Laboratory of Modeling and Biostatistics,
Pasteur Institute of Algeria) |
| Maintainer: |
Nassim AYAD <nassim.ayad.ph at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
EvalTest results |
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