mc.PBequi: Equivariant Passing-Bablok Regression

In mcr: Method Comparison Regression

Equivariant Passing-Bablok Regression

Description

This is an implementation of the equivariant Passing-Bablok regression.

Usage

mc.PBequi(
  X,
  Y,
  alpha = 0.05,
  slope.measure = c("radian", "tangent"),
  method.reg = c("PBequi", "TS"),
  extended.output = FALSE,
  calcCI = TRUE,
  methodlarge = TRUE
)

Arguments

X	measurement values of reference method
Y	measurement values of test method
alpha	numeric value specifying the 100(1-alpha)% confidence level
slope.measure	angular measure of pairwise slopes (see mcreg for details). "radian" - for data sets with even sample numbers median slope is calculated as average of two central slope angles. "tangent" - for data sets with even sample numbers median slope is calculated as average of two central slopes (tan(angle)).
method.reg	"PBequi" equivariant Passing-Bablok regression; "TS" Theil-Sen regression
extended.output	boolean. If TRUE, several intermediate results are returned
calcCI	boolean. If TRUE, sd of intercept and slope as well as xw are calculated
methodlarge	If TRUE (default), quasilinear method is used, if FALSE, quadratic method is used

Value

a list with elements.

b0	intercept.
b1	slope.
se.b0	respective standard error of intercept.
se.b1	respective standard error of slope.
xw	weighted average of reference method values.
weight	dummy values, only returned it extended.output=FALSE.
sez	variance of intercept for fixed slope (extended.output=TRUE, only).
vartau	variance of Kendall's tau (extended.output=TRUE, only).
covtx	covariance of tau and zeta (extended.output=TRUE, only).
x0	"center of gravity" of x (extended.output=TRUE, only).
taui	"Inversion vector; Indicator of influence"

mcr documentation built on Oct. 11, 2023, 5:14 p.m.