bayesdca: Bayesian Decision Curve Analysis

In sbalci/ClinicoPathJamoviModule: Analysis for Clinicopathological Research

Bayesian Decision Curve Analysis

Description

Bayesian Decision Curve Analysis

Usage

bayesdca(
  data,
  outcomes,
  outcomePos,
  predictors,
  thresholdMin = 0.01,
  thresholdMax = 0.5,
  thresholdPoints = 50,
  useExternalPrevalence = FALSE,
  externalCases = 100,
  externalTotal = 500,
  bayesianAnalysis = TRUE,
  priorStrength = 2,
  bootstrapCI = TRUE,
  bootstrapReps = 2000,
  calculateEVPI = FALSE,
  nDraws = 2000,
  directionIndicator = ">="
)

Arguments

data	The data as a data frame.
outcomes	Binary outcome variable (0/1) representing the true disease status or event.
outcomePos	Specifies which level of the outcome variable should be treated as the positive class.
predictors	Variables containing either probability predictions from models or binary results (0/1) from diagnostic tests.
thresholdMin	Minimum decision threshold for the analysis.
thresholdMax	Maximum decision threshold for the analysis.
thresholdPoints	Number of threshold points to evaluate.
useExternalPrevalence	Use external prevalence data instead of sample prevalence.
externalCases	Number of cases in external prevalence data.
externalTotal	Total sample size in external prevalence data.
bayesianAnalysis	Perform Bayesian analysis with uncertainty quantification.
priorStrength	Strength of prior (effective sample size).
bootstrapCI	Calculate bootstrap confidence intervals for non-Bayesian analysis.
bootstrapReps	Number of bootstrap replications for confidence intervals.
calculateEVPI	Calculate Expected Value of Perfect Information.
nDraws	Number of posterior draws for Bayesian analysis.
directionIndicator	Direction of classification relative to the cutpoint. Use '>=' when higher values predict positive outcomes.

Value

A results object containing:

results$instructions					a html
results$summary					a html
results$netBenefitTable					a table
results$modelResults					an array of tables
results$comparisonTable					a table
results$evpiTable					a table
results$mainPlot					an image
results$deltaPlot					an image
results$probPlot					an image
results$evpiPlot					an image

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

results$netBenefitTable$asDF

as.data.frame(results$netBenefitTable)

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