std.test

The <code>std.test</code> Standardization parameters will be taken
from the fitted training model and applied to the new data set.

A system for combining two diagnostic tests using various approaches
that include statistical and machine-learning-based methodologies.
These approaches are divided into four groups: linear combination
methods, non-linear combination methods, mathematical operators,
and machine learning algorithms. See
the <https://biotools.erciyes.edu.tr/dtComb/> website
for more information, documentation, and examples.

Gokmen Zararsiz

dtComb

Statistical Combination of Diagnostic Tests

Serra Ilayda Yerlitas

Serra Bersan Gengec

Necla Kochan

Gozde Erturk Zararsiz

Selcuk Korkmaz

std.test function

<dl><dt>newdata</dt>
<dd>a <code>numeric</code> data frame of biomarkers</dd>
<dt>model</dt>
<dd>a <code>list</code> of parameters from the output of linComb,
nonlinComb, mlComb or mathComb functions.</dd></dl>

Arguments

Serra Ilayda Yerlitas, Serra Bersan Gengec, Necla Kochan,
Gozde Erturk Zararsiz, Selcuk Korkmaz, Gokmen Zararsiz

Author

Standardization according to the training model parameters. — std.test

<dl>

<dt>newdata</dt>
<dd>a <code>numeric</code> data frame of biomarkers</dd>


<dt>model</dt>
<dd>a <code>list</code> of parameters from the output of linComb,
nonlinComb, mlComb or mathComb functions.</dd>

</dl>

std.test: Standardization according to the training model parameters.

Description

Usage

Value

Arguments

Author