mcreg: Comparison of Two Measurement Methods Using Regression...

In mcradds: Processing and Analyzing of Diagnostics Trials

Comparison of Two Measurement Methods Using Regression Analysis

Description

A copy from mcr::mcreg in mcr package

Usage

mcreg(...)

Arguments

...

Arguments passed on to mcr::mcreg x measurement values of reference method, or two column matrix. y measurement values of test method. error.ratio ratio between squared measurement errors of reference and test method, necessary for Deming regression (Default 1). alpha value specifying the 100(1-alpha)% confidence level for confidence intervals (Default is 0.05). mref.name name of reference method (Default "Method1"). mtest.name name of test Method (Default "Method2"). sample.names names of cases (Default "S##"). method.reg regression method. It is possible to choose between five regression methods: "LinReg" - ordinary least square regression. "WLinReg" - weighted ordinary least square regression. "Deming" - Deming regression. "WDeming" - weighted Deming regression. "TS" - Theil-Sen regression. "PBequi" - equivariant Passing-Bablok regression. "PaBa" - Passing-Bablok regression. "PaBaLarge" - approximative Passing-Bablok regression for large datasets, operating on NBins classes of constant slope angle which each slope is classified to instead of building the complete triangular matrix of all N*N/2 slopes. method.ci method of confidence interval calculation. The function contains four basic methods for calculation of confidence intervals for regression coefficients. "analytical" - with parametric method. "jackknife" - with leave one out resampling. "bootstrap" - with ordinary non-parametric bootstrap resampling. "nested bootstrap" - with ordinary non-parametric bootstrap resampling. method.bootstrap.ci bootstrap based confidence interval estimation method. nsamples number of bootstrap samples. nnested number of nested bootstrap samples. rng.seed integer number that sets the random number generator seed for bootstrap sampling. If set to NULL currently in the R session used RNG setting will be used. rng.kind type of random number generator for bootstrap sampling. Only used when rng.seed is specified, see set.seed for details. iter.max maximum number of iterations for weighted Deming iterative algorithm. threshold numerical tolerance for weighted Deming iterative algorithm convergence. na.rm remove measurement pairs that contain missing values (Default is FALSE). NBins number of bins used when 'reg.method="PaBaLarge"' to classify each slope in one of 'NBins' bins covering the range of all slopes slope.measure angular measure of pairwise slopes used for exact PaBa regression (see below 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)). methodlarge Boolean. This parameter applies only to regmethod="PBequi" and "TS". If TRUE, a quasilinear algorithm is used. If FALSE, a quadratic algorithm is used which is faster for less than several hundred data pairs.

Value

A regression fit model.

See Also

mcr::mcreg()

Examples

data(platelet)
fit <- mcreg(
  x = platelet$Comparative, y = platelet$Candidate,
  method.reg = "Deming", method.ci = "jackknife"
)
printSummary(fit)
getCoefficients(fit)

mcradds documentation built on Sept. 11, 2024, 5:33 p.m.