mc.analytical.ci

Calculate wald confidence intervals for intercept and slope
given point estimates and 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.analytical.ci function

<dl><dt>b0</dt>
<dd>point estimate of intercept.</dd>
<dt>b1</dt>
<dd>point estimate of slope.</dd>
<dt>se.b0</dt>
<dd>standard error of intercept.</dd>
<dt>se.b1</dt>
<dd>standard error of slope.</dd>
<dt>n</dt>
<dd>number of observations.</dd>
<dt>alpha</dt>
<dd>numeric value specifying the 100(1-alpha)% confidence level for the confidence interval (Default is 0.05).</dd></dl>

Arguments

Analytical Confidence Interval — mc.analytical.ci

<dl>

<dt>b0</dt>
<dd>point estimate of intercept.</dd>


<dt>b1</dt>
<dd>point estimate of slope.</dd>


<dt>se.b0</dt>
<dd>standard error of intercept.</dd>


<dt>se.b1</dt>
<dd>standard error of slope.</dd>


<dt>n</dt>
<dd>number of observations.</dd>


<dt>alpha</dt>
<dd>numeric value specifying the 100(1-alpha)% confidence level for the confidence interval (Default is 0.05).</dd>

</dl>

mc.analytical.ci: Analytical Confidence Interval

Description

Usage

Value

Arguments