Medical Decision Calculator

Medical Decision Calculator for diagnostic test evaluation when you have the four key counts: True Positives (TP), False Positives (FP), True Negatives (TN), and False Negatives (FN). Calculates comprehensive diagnostic performance metrics including sensitivity, specificity, positive and negative predictive values, likelihood ratios, and post-test probabilities. Supports confidence interval estimation and Fagan nomogram visualization for clinical decision making.

Usage

decisioncalculator(
  TP = 90,
  TN = 80,
  FP = 30,
  FN = 20,
  pp = FALSE,
  pprob = 0.3,
  fnote = FALSE,
  ci = FALSE,
  fagan = FALSE
)

Arguments

TP

.

TN

.

FP

.

FN

.

pp

.

pprob

Prior probability (disease prevalence in the community). Requires a value between 0.001 and 0.999, default 0.300.

fnote

.

ci

.

fagan

.

Value

A results object containing:

results$cTable					a table
results$nTable					a table
results$ratioTable					a table
results$epirTable_ratio					a table
results$epirTable_number					a table
results$plot1					an image

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$cTable$asDF

as.data.frame(results$cTable)

Examples

# Basic diagnostic test evaluation with known counts
result1 <- decisioncalculator(
  TP = 90,  # True positives
  FN = 10,  # False negatives
  TN = 80,  # True negatives
  FP = 20   # False positives
)

# Include 95\% confidence intervals
result2 <- decisioncalculator(
  TP = 90, FN = 10, TN = 80, FP = 20,
  ci = TRUE
)

# Complete analysis with Fagan nomogram
result3 <- decisioncalculator(
  TP = 90, FN = 10, TN = 80, FP = 20,
  ci = TRUE, pp = TRUE, pprob = 0.15, fagan = TRUE
)