ppwdeming (version 1.0.6)

WD_Linnet: 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)

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

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.

Author

Douglas M. Hawkins, Jessica J. Kraker

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")