Title: A 'shiny' App to Evaluate Diagnostic Tests Performance
Version: 1.0.2
Maintainer: Nassim AYAD <nassim.ayad.ph@gmail.com>
Description: 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.
Depends: R (≥ 4.2.1)
Imports: DT, ggplot2, ggpubr, openxlsx, pROC, readxl, shiny, shinydashboard, stats, binom
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-09-09 19:58:34 UTC; maison
Author: Nassim AYAD ORCID iD [aut, cre] (affiliation: Laboratory of Modeling and Biostatistics, Pasteur Institute of Algeria)
Repository: CRAN
Date/Publication: 2025-09-14 16:20:19 UTC

Compute diagnostic test indicators

Description

This function computes sensitivity, specificity, predictive values, likelihood ratios, accuracy, and Youden index with confidence intervals based on a 2x2 table of diagnostic test results.

Usage

compute_indicators(tp, fp, fn, tn, prev, conf = 0.95)

Arguments

tp

True positives

fp

False positives

fn

False negatives

tn

True negatives

prev

Prevalence (numeric between 0 and 1)

conf

Confidence level (default 0.95)

Value

A list with all diagnostic indicators and confidence intervals

Examples

compute_indicators(50, 10, 5, 100, prev = 0.1)

Launch the EvalTest Shiny application

Description

This function starts the Shiny application included in the EvalTest package, which aims to evaluate diagnostic tests performance.

Usage

run_app()

Value

The function does not return a value; it launches a Shiny application.

Examples

if (interactive()) {
  library(EvalTest)
  run_app()
}

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