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mcr (version 1.3.3.1)

mc.PBequi: 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
)

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"

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