refineR (version 2.0.0)

verifyRI: Verify Reference Intervals

Description

This function verifies the reference intervals based on the provided data.

Usage

verifyRI(
  RIdata,
  RIcand,
  RIperc = c(0.025, 0.975),
  UMprop = 0.9,
  pointEst = c("fullDataEst", "medianBS"),
  printResults = TRUE,
  generatePlot = TRUE,
  Scale = c("original", "transformed", "splitXAxis"),
  xlab = NULL,
  title = NULL,
  verbose = TRUE,
  ...
)

Value

		(list) containing the verification results

Arguments

RIdata

specifying the RI of the local population: (1) (object) of class RWDRI or (2) (numeric) representation of reference limits

RIcand

specifying the RI that needs to be verified: (1) (object) of class RWDRI or (2) (numeric) representation of reference limits

RIperc

(numeric) value specifying the percentiles, which define the reference interval (default c(0.025, 0.975))

UMprop

(numeric) specifying the width of the confidence interval approximated by the uncertainty margins (default 0.9)

pointEst

(character) specifying the point estimate determination: (1) using the full dataset ("fullDataEst"), (2) calculating the median model from the bootstrap samples ("medianBS"), (2) works only if NBootstrap > 0

printResults

(logical) if TRUE, results are printed in the console.

generatePlot

(logical) if TRUE, a plot is generated.

Scale

(character) specifying the scale of the plot: (1) "original", (2) "transformed", (3) "splitXAxis"

xlab

(character) optional x-axis label for the plot

title

(character) optional title for the plot

verbose

(logical) specifying if additional warning messages are printed

...

(list) specifying non-default parameters for the calculation of the margins

Author

Matthias Beck

Examples

if (FALSE) {

# standard usecase: 
# comparison of the RI estimated from the local population with a numeric candidate
# RI from, e.g., literature
RIdata <- findRI(testcase1)
RIcand <- c(10, 20)
verifyRI(RIdata, RIcand, RIperc = c(0.025, 0.975))

# Test if two refineR models are equivalent with stricter criteria, i.e., larger n
model1 <- list(Mu = 20, Sigma = 11, Shift = 8, Lambda = 1,
							Method = "manual", roundingBase = NA)
model2 <- list(Mu = 3.41, Sigma = 0.504, Shift = 1, Lambda = 0.06,
							Method = "manual", roundingBase = NA)
class(model1) <- class(model2) <- "RWDRI"
verifyRI(RIdata = model1, RIcand = model2, UMprop = 0.95, n = 1e4)

# verify two numeric RIs
verifyRI(RIdata = c(2.4, 28), RIcand = c(3.1, 29.75))
}