Skip to contents

All functions

agreement()
Interrater Reliability
agreementClass
Interrater Reliability Analysis
auc_ci()
Statistical Utility Functions
bootstrapIDI()
Bootstrap IDI calculation with confidence intervals
bootstrapNRI()
Bootstrap NRI calculation with confidence intervals
bootstrap_ci()
Bootstrap confidence intervals for diagnostic metrics
calculateCEAC()
Calculate Cost-Effectiveness Acceptability Curve (CEAC)
calculateEVPI()
Calculate Expected Value of Perfect Information (EVPI)
calculateMarkovTransitionMatrix()
Calculate Markov Transition Matrix
calculate_auc()
Calculate AUC from sensitivity and specificity
calculate_nlr()
Calculate negative likelihood ratio
calculate_npv()
Calculate negative predictive value (NPV)
calculate_plr()
Calculate positive likelihood ratio
calculate_ppv()
Calculate positive predictive value (PPV)
calculate_sensitivity()
Calculate diagnostic sensitivity
calculate_specificity()
Calculate diagnostic specificity
clinicopath_startup_message()
Package startup message
computeNRI()
Compute Net Reclassification Index (NRI)
cotest()
Co-Testing Analysis
cotestClass
Co-Testing Analysis
createSafeHTMLContent()
Create Error-Safe HTML Content
decision()
Medical Decision
decisionClass
Medical Decision Analysis
decisioncalculator()
Medical Decision Calculator
decisioncalculatorClass
Decision Calculator
decisioncombine()
Combine Medical Decision Tests
decisioncombineClass
Combine Medical Decision Tests
decisioncompare()
Compare Medical Decision Tests
decisioncompareClass
Compare Medical Decision Tests
.escapeVariableNames()
Analysis Without Gold Standard
enhancedROC()
Clinical ROC Analysis
enhancedROCClass
Enhanced ROC Analysis Class
is_in_range()
Check if value is within valid range
kappaSizeCI()
Confidence Interval Approach for the Number of Subjects Required
kappaSizeCIClass
Confidence Interval Approach for the Number of Subjects Required
kappaSizeFixedN()
Lowest Expected Value for a fixed sample size
kappaSizeFixedNClass
Lowest Expected Value for a fixed sample size
kappaSizePower()
Power Approach for the Number of Subjects Required
kappaSizePowerClass
Power Approach for the Number of Subjects Required
load_required_package()
Load required packages with error handling
meddecide-package meddecide
Functions for Medical Decision Making in ClinicoPath jamovi Module
nogoldstandard()
Analysis Without Gold Standard
nomogrammer()
Fagan Nomogram for Diagnostic Test Analysis
performMonteCarloSimulation()
Perform Monte Carlo Simulation for PSA
print(<sensSpecTable>)
Print formatted HTML table for sensitivity/specificity results
prop_to_percent()
Convert proportion to percentage string
psychopdaROC()
Advanced ROC Analysis
psychopdaROCClass
Comprehensive ROC Analysis with Advanced Features
raw_to_prob()
Convert raw test values to predicted probabilities using ROC curve
safe_divide()
Safe division function
sequentialtests()
Sequential Testing Analysis
sequentialtestsClass
Sequential Testing Analysis
validateDecisionAnalysisInputs()
Validate Decision Analysis Inputs
validateROCInputs()
Validate inputs for ROC analysis