mc.calc.quantile

Calculate bootstrap confidence intervals for intercept, slope or bias
given the vector of bootstrap point estimates.

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

Roche 

mc.calc.quantile function

<dl><dt>Xboot</dt>
<dd>vector of point estimates for bootstrap samples. 
The i-th element contains point estimate of the i-th bootstrap sample.</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

Quantile Method for Calculation of Resampling Confidence Intervals — mc.calc.quantile

<dl>

<dt>Xboot</dt>
<dd>vector of point estimates for bootstrap samples. 
The i-th element contains point estimate of the i-th bootstrap sample.</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.calc.quantile: Quantile Method for Calculation of Resampling Confidence Intervals

Description

Usage

Value

Arguments

References