decisioncurve: Decision Curve Analysis

In sbalci/ClinicoPathJamoviModule: Analysis for Clinicopathological Research

Decision Curve Analysis

Description

Decision Curve Analysis for evaluating the clinical utility of prediction models and diagnostic tests. Calculates net benefit across threshold probabilities to determine if using a model provides more benefit than default strategies.

Usage

decisioncurve(
  data,
  outcome,
  outcomePositive,
  models,
  modelNames = "",
  thresholdRange = "clinical",
  thresholdMin = 0.05,
  thresholdMax = 0.5,
  thresholdStep = 0.01,
  showTable = TRUE,
  selectedThresholds = "0.05, 0.10, 0.15, 0.20, 0.25, 0.30",
  showPlot = TRUE,
  plotStyle = "standard",
  showReferenceLinesLabels = TRUE,
  highlightRange = FALSE,
  highlightMin = 0.1,
  highlightMax = 0.3,
  calculateClinicalImpact = FALSE,
  populationSize = 1000,
  showInterventionAvoided = FALSE,
  confidenceIntervals = FALSE,
  bootReps = 1000,
  ciLevel = 0.95,
  showOptimalThreshold = TRUE,
  compareModels = FALSE,
  weightedAUC = FALSE
)

Arguments

data	The data as a data frame.
outcome	Binary outcome variable (0/1 or FALSE/TRUE). This represents the condition or event you want to predict.
outcomePositive	Which level of the outcome variable represents the positive case (presence of condition/event).
models	Variables representing predicted probabilities or risk scores from different models. Can include multiple models for comparison.
modelNames	Optional comma-separated list of names for the models. If not provided, variable names will be used.
thresholdRange	Range of threshold probabilities to evaluate.
thresholdMin	Minimum threshold probability when using custom range.
thresholdMax	Maximum threshold probability when using custom range.
thresholdStep	Step size between threshold probabilities.
showTable	Display table with net benefit values at selected thresholds.
selectedThresholds	Comma-separated list of threshold probabilities to display in table.
showPlot	Display the decision curve plot.
plotStyle	Style of the decision curve plot.
showReferenceLinesLabels	Show labels for "Treat All" and "Treat None" reference lines.
highlightRange	Highlight a clinically relevant threshold range on the plot.
highlightMin	Minimum threshold for highlighted range.
highlightMax	Maximum threshold for highlighted range.
calculateClinicalImpact	Calculate clinical impact metrics (number needed to screen, etc.).
populationSize	Population size for calculating clinical impact metrics.
showInterventionAvoided	Show how many unnecessary interventions are avoided compared to treat-all.
confidenceIntervals	Calculate bootstrap confidence intervals for net benefit curves.
bootReps	Number of bootstrap replications for confidence intervals.
ciLevel	Confidence level for bootstrap confidence intervals.
showOptimalThreshold	Identify and display optimal threshold probabilities for each model.
compareModels	Calculate statistical tests for comparing model performance.
weightedAUC	Calculate weighted area under the decision curve.

Value

A results object containing:

results$instructions					a html
results$procedureNotes					a html
results$resultsTable					a table
results$optimalTable					a table
results$clinicalImpactTable					a table
results$comparisonTable					a table
results$weightedAUCTable					a table
results$dcaPlot					an image
results$clinicalImpactPlot					an image
results$interventionsAvoidedPlot					an image
results$summaryText					a html

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

results$resultsTable$asDF

as.data.frame(results$resultsTable)

Examples

# example will be added

sbalci/ClinicoPathJamoviModule documentation built on June 13, 2025, 9:34 a.m.