ROC Analysis with Diagnostic Accuracy Tools for Jamovi
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Updated
Nov 18, 2025 - R
ROC Analysis with Diagnostic Accuracy Tools for Jamovi
This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.
A Shiny Application to Evaluate Diagnostic Tests Performance. It allows users to compute key performance indicators and visualize ROC curves, determine optimal cut-off thresholds, display confusion matrix, and export publication-ready plots. It supports both binary and continuous test variables.
Display and analyze ROC curves in R
Bioinformatics consultancy on MS-MLPA data analysis | Consultoria em Bioinformática para análise de dados de MS-MLPA
This is a tutorial analysing a fake study. The tutorial is aimed at people broadly familiar with basic stats, but who need a hand adapting this to R, and who are motivated to learn to code in R. More specifically, it looks at participant characteristics/descriptive stats, basic hypothesis testing, logistic regression, and ROC curve analysis
R package 'wROC'. Estimation of the ROC curve and AUC with complex survey data.
BEGINNER - This is a classification project for the subject "Data Mining" in the 3rd year of Statistics (SSE) at the University of Milano-Bicocca.
ROC-GLM and calibration analysis for DataSHIELD
University of Tehran - Spring 2020
mewto is an R package that allows you to experiment with different thresholds for classification of prediction results in the case of binary classification problems and visualize various model evaluation metrics, confusion matrices and the ROC curve. It also allows you to calculate the optimal threshold based on a weighted evaluation criterion.
Includes a package for rank order clustering and modified rank order clustering proposed by Amruthnath (2016)
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