mc.bootstrap: Resampling estimation of regression parameters and standard...

In mcr: Method Comparison Regression

Resampling estimation of regression parameters and standard errors.

Description

Generate jackknife or (nested-) bootstrap replicates of a statistic applied to data. Only a nonparametric ballanced design is possible. For each sample calculate point estimations and standard errors for regression coefficients.

Usage

mc.bootstrap(
  method.reg = c("LinReg", "WLinReg", "Deming", "WDeming", "PaBa", "PaBaLarge", "TS",
    "PBequi"),
  jackknife = TRUE,
  bootstrap = c("none", "bootstrap", "nestedbootstrap"),
  X,
  Y,
  error.ratio,
  nsamples = 1000,
  nnested = 25,
  iter.max = 30,
  threshold = 1e-08,
  NBins = 1e+06,
  slope.measure = c("radian", "tangent")
)

Arguments

method.reg	Regression method. It is possible to choose between five regression types: "LinReg" - ordinary least square regression, "WLinReg" - weighted ordinary least square regression,"Deming" - Deming regression, "WDeming" - weighted Deming regression, "PaBa" - Passing-Bablok regression.
jackknife	Logical value. If TRUE - Jackknife based confidence interval estimation method.
bootstrap	Bootstrap based confidence interval estimation method.
X	Measurement values of reference method
Y	Measurement values of test method
error.ratio	Ratio between squared measurement errors of reference- and test method, necessary for Deming regression. Default 1.
nsamples	Number of bootstrap samples.
nnested	Number of nested bootstrap samples.
iter.max	maximum number of iterations for weighted Deming iterative algorithm.
threshold	Numerical tolerance for weighted Deming iterative algorithm convergence.
NBins	number of bins used when 'reg.method="PaBaLarge"' to classify each slope in one of 'NBins' bins of constant slope angle covering the range of all slopes.
slope.measure	angular measure of pairwise slopes used for exact PaBa regression (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)).

Value

a list consisting of

glob.coef	Numeric vector of length two with global point estimations of intercept and slope.
glob.sigma	Numeric vector of length two with global estimations of standard errors of intercept and slope.
xmean	Global (weighted-)average of reference method values.
B0jack	Numeric vector with point estimations of intercept for jackknife samples. The i-th element contains point estimation for data set without i-th observation
B1jack	Numeric vector with point estimations of slope for jackknife samples. The i-th element contains point estimation for data set without i-th observation
B0	Numeric vector with point estimations of intercept for each bootstrap sample. The i-th element contains point estimation for i-th bootstrap sample.
B1	Numeric vector with point estimations of slope for each bootstrap sample. The i-th element contains point estimation for i-th bootstrap sample.
MX	Numeric vector with point estimations of (weighted-)average of reference method values for each bootstrap sample. The i-th element contains point estimation for i-th bootstrap sample.
sigmaB0	Numeric vector with estimation of standard error of intercept for each bootstrap sample. The i-th element contains point estimation for i-th bootstrap sample.
sigmaB1	Numeric vector with estimation of standard error of slope for each bootstrap sample. The i-th element contains point estimation for i-th bootstrap sample.
nsamples	Number of bootstrap samples.
nnested	Number of nested bootstrap samples.
cimeth	Method of confidence interval calculation (bootstrap).
npoints	Number of observations.

Author(s)

Ekaterina Manuilova [e-mail], Fabian Model [e-mail], Sergej Potapov [e-mail]

References

Efron, B., Tibshirani, R.J. (1993) An Introduction to the Bootstrap. Chapman and Hall. Carpenter, J., Bithell, J. (2000) Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians. Stat Med, 19 (9), 1141–1164.

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