Medical Decision Calculator

Usage

decisioncalculator(
  TP = 90,
  TN = 80,
  FP = 30,
  FN = 20,
  pp = FALSE,
  pprob = 0.3,
  fnote = FALSE,
  ci = FALSE,
  fagan = FALSE,
  showWelcome = TRUE,
  showSummary = FALSE,
  showAbout = FALSE,
  showGlossary = FALSE,
  multiplecuts = FALSE,
  cutoff1 = "Conservative",
  tp1 = 85,
  fp1 = 10,
  tn1 = 190,
  fn1 = 15,
  cutoff2 = "Aggressive",
  tp2 = 95,
  fp2 = 25,
  tn2 = 175,
  fn2 = 5
)

Arguments

TP

True Positive count: cases with disease that tested positive.

TN

True Negative count: cases without disease that tested negative.

FP

False Positive count: cases without disease that tested positive.

FN

False Negative count: cases with disease that tested negative.

pp

Boolean selection whether to use known population prevalence.

pprob

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

fnote

Boolean selection whether to show detailed explanatory footnotes.

ci

Boolean selection whether to calculate 95\

faganBoolean selection whether to generate a Fagan nomogram plot.

showWelcomeBoolean selection whether to show welcome message.

showSummaryBoolean selection whether to show plain-language summary of results.

showAboutBoolean selection whether to show about and assumptions panels.

showGlossaryBoolean selection whether to show clinical glossary.

multiplecutsBoolean selection whether to evaluate multiple cut-off scenarios.

cutoff1Name identifier for cut-off scenario 1.

tp1.

fp1.

tn1.

fn1.

cutoff2Name identifier for cut-off scenario 2.

tp2.

fp2.

tn2.

fn2.

A results object containing:

results$welcome					a html
results$summary					a html
results$about					a html
results$assumptions					a html
results$glossary					a html
results$cTable					a table
results$nTable					a table
results$ratioTable					a table
results$advancedMetricsTable					a table
results$epirTable_ratio					a table
results$epirTable_number					a table
results$plot1					an image
results$multipleCutoffTable					a table

Tables can be converted to data frames with asDF or as.data.frame. For example:results$cTable$asDFas.data.frame(results$cTable) 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. # 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\ 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 )