Package 'EvalTest'

Title: Tools for Evaluating Diagnostic Test Performance
Description: Evaluates diagnostic test performance using data from laboratory or diagnostic research. It includes functions to compute common performance indicators along with their confidence intervals, and offers an interactive 'shiny' application for comprehensive analysis including ROC curve visualization and related metrics. 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. Methodological details and references for the computation of performance indicators are provided in the package vignette.
Authors: Nassim AYAD [aut, cre] (ORCID: <https://orcid.org/0000-0002-1809-0935>, affiliation: Laboratory of Modeling and Biostatistics, Pasteur Institute of Algeria)
Maintainer: Nassim AYAD <[email protected]>
License: MIT + file LICENSE
Version: 1.0.6
Built: 2026-05-22 08:24:15 UTC
Source: https://github.com/nassimayad87/evaltest

Help Index

Compute diagnostic test indicators

Description

This function computes sensitivity, specificity, predictive values, likelihood ratios, accuracy, and Youden index with their confidence intervals (with desired confidence level), 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(58, 15, 14, 26, prev = 0.1, conf = 0.95)

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()
}