Package index • meddecide

All functions

agreement(): Interrater Reliability

agreementClass: Comprehensive 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

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)

decision(): Medical Decision

decisionClass: Medical Decision Analysis

decisioncalculator(): Medical Decision Calculator

decisioncalculatorClass: Decision Calculator

decisioncompare(): Compare Medical Decision Tests

decisioncompareClass: Compare Medical Decision Tests

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

nogoldstandardClass: Analysis Without Gold Standard

nomogrammer(): Fagan Nomogram for Diagnostic Test Analysis

print(<sensSpecTable>): Print formatted HTML table for sensitivity/specificity results

prop_to_percent(): Convert proportion to percentage string

psychopdaroc(): 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

validateROCInputs(): Validate inputs for ROC analysis