mc.deming

Calculate Unweighted Deming Regression and Estimate Standard Errors

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 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>).
A comprehensive overview over the implemented methods and references can be found
in the manual pages "mcr-package" and "mcreg".

Sergej Potapov

Method Comparison Regression

Fabian Model

Andre Schuetzenmeister

Ekaterina Manuilova

Florian Dufey

Jakob Raymaekers

Venkatraman E. Seshan

Roche 

mc.deming function

<dl><dt>X</dt>
<dd>measurement values of reference method.</dd>
<dt>Y</dt>
<dd>measurement values of test method.</dd>
<dt>error.ratio</dt>
<dd>ratio of measurement error of reference method to measurement error of test method.</dd></dl>

Arguments

Calculate Unweighted Deming Regression and Estimate Standard Errors — mc.deming

<dl>

<dt>X</dt>
<dd>measurement values of reference method.</dd>


<dt>Y</dt>
<dd>measurement values of test method.</dd>


<dt>error.ratio</dt>
<dd>ratio of measurement error of reference method to measurement error of test method.</dd>

</dl>

mc.deming: Calculate Unweighted Deming Regression and Estimate Standard Errors

Description

Usage

Value

Arguments

References