gg_diagnostic_prev: Diagnostic Prevalence

In TalhoukLab/biostatUtil: Utility Functions Used in Biostatistics Projects

Diagnostic Prevalence

Description

Compare PPV or NPV by sensitivity, specificity, and prevalence.

Usage

gg_diagnostic_prev(se, sp, p, result = c("PPV", "NPV"))

gg_prev_fixed(se, sp, p, result = c("PPV", "NPV"), layout = c("lines", "band"))

Arguments

se	a vector of sensitivity estimates. For gg_prev_fixed, must be a vector of length 3 for lower bound, pooled estimate, and upper bound.
sp	a vector of specificity estimates. For gg_prev_fixed, must be a vector of length 3 for lower bound, pooled estimate, and upper bound. For gg_diagnostic_prev, a sequence of values to plot along x-axis.
p	a vector of prevalence values. For gg_prev_fixed, must be a sequence of values to plot along x-axis.
result	whether to show the PPV or NPV on the y-axis
layout	whether to plot confidence region using "lines" or a filled "band."

Details

gg_diagnostic_prev plots positive predictive value (PPV) or negative predictive value (NPV) as a function of specificity, with sensitivity separated by line types and prevalence shown across facets.

gg_prev_fixed plots PPV or NPV as a function of prevalence, with coloured lines separating fixed pairs of sensitivity and specificity for the lower bound, pooled estimate, and upper bound.

Value

Graph of PPV or NPV by specificity, sensitivity, and prevalence.

Author(s)

Derek Chiu

Examples

se <- c(0.5, 0.7, 0.9)
sp <- seq(0.21, 1, 0.01)
p <- c(0.32, 0.09, 0.026)
gg_diagnostic_prev(se, sp, p, result = "PPV")
gg_diagnostic_prev(se, sp, p, result = "NPV")

gg_prev_fixed(
  se = c(0.67, 0.83, 0.97),
  sp = c(0.86, 0.94, 0.99),
  p = seq(0.01, 0.30, 0.01),
  result = "PPV"
)

TalhoukLab/biostatUtil documentation built on April 14, 2025, 4:15 a.m.