MCResultResampling.plotBoxEllipses

Plot Box Ellipses of bootstrap coefficients (slope and intercept).

Regression methods to quantify the relation between two measurement
methods are provided by this package. In particular it addresses regression
problems with errors in both variables and without repeated measurements. It
implements the Clinical Laboratory Standard International (CLSI)
recommendations (see J. A. Budd et al.
(2018, <https://clsi.org/standards/products/method-evaluation/documents/ep09/>)
for analytical method comparison and bias estimation using patient samples.
Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators
are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and
J. Raymaekers and F. Dufey (2022, <arXiv:2202:08060>).
Further the robust M-Deming and MM-Deming (experimental) are available, see
G. Pioda (2021, <arXiv:2105:04628>).
A comprehensive overview over the implemented methods and references can be found
in the manual pages 'mcrPioda-package' and 'mcreg'.

Giorgio Pioda

mcrPioda

Method Comparison Regression - Mcr Fork for M- And MM-Deming
Regression

Sergej Potapov

Fabian Model

Andre Schuetzenmeister

Ekaterina Manuilova

Florian Dufey

Jakob Raymaekers

Venkatraman E. Seshan

Roche 

MCResultResampling.plotBoxEllipses function

<dl><dt>.Object</dt>
<dd>Object of class "MCResultResampling"</dd>
<dt>robust.cov</dt>
<dd>Method for covariance. Default "MCD"</dd></dl>

Arguments

Plot Box Ellipses of bootstrap coefficients — MCResultResampling.plotBoxEllipses

<dl>

<dt>.Object</dt>
<dd>Object of class "MCResultResampling"</dd>


<dt>robust.cov</dt>
<dd>Method for covariance. Default "MCD"</dd>

</dl>

Plot Box Ellipses of bootstrap coefficients

MCResultResampling.plotBoxEllipses: Plot Box Ellipses of bootstrap coefficients

Description

Usage

Value

Arguments