WD_Linnet: Linnet proportional CV weighted Deming

In ppwdeming: Precision Profile Weighted Deming Regression

Linnet proportional CV weighted Deming

Description

This routine, provided for convenience, makes Linnet’s constant CV fit.

Usage

WD_Linnet(X, Y, lambda=1, MDL=NA, getCI=TRUE, epsilon=1e-9, printem=FALSE)

Arguments

X	the vector of predicate readings,
Y	the vector of test readings,
lambda	ratio of g function to h function,
MDL	optional medical decision limit(s),
getCI	if TRUE, generates jackknife standard errors,
epsilon	optional tolerance limit,
printem	if TRUE, prints out results as a message.

Value

A list containing the following components:

alpha	the fitted intercept
beta	the fitted slope
cor	the Pearson correlation between X and Y
sealpha	the jackknife standard error of alpha
sebeta	the jackknife standard error of beta
covar	the jackknife covariance between alpha and beta
preMDL	the predictions at the MDL(s)
preMDLl	the lower confidence limit(s) of preMDL
preMDLu	the upper confidence limit(s) of preMDL

Author(s)

Douglas M. Hawkins, Jessica J. Kraker [e-mail]

References

Linnet K (1993). Evaluation of regression procedures for methods comparison studies. Clinical Chemistry, 39, 424-432.

Examples

# library
library(ppwdeming)

# parameter specifications
alpha <- 1
beta  <- 1.1
true  <- 8*10^((0:99)/99)
truey <- alpha+beta*true
kappa <- 0.1

# simulate single sample - set seed for reproducibility
set.seed(1039)
# specifications for predicate method
X     <- true *(1+kappa*rnorm(100))
# specifications for test method
Y     <- truey *(1+kappa*rnorm(100))

# fit with to estimate linear parameters
wd_fit <- WD_Linnet(X, Y, MDL=12, printem=TRUE)
cat("\nThe Linnet constant-CV estimated intercept is",
    signif(wd_fit$alpha,4), "and the estimated slope is",
    signif(wd_fit$beta,4), "\n")

ppwdeming documentation built on Sept. 9, 2025, 5:37 p.m.