droplevels.mic_validation

Quite often, MIC values are being compared across methods with different
levels of granularity. For example, the true MIC may be measured across a
higher range of values than the test method. This means that there may be
MIC levels that don't provide much additional information (since they are
only present in one of the methods). This function removes these unnecessary
levels at both ranges of the MIC values.
This function ensure that the changes do not "change" the essential
agreement interpretation. This can be suppressed using safe = FALSE,
however this is probably not desired behaviour.

Analyse, plot, and tabulate antimicrobial minimum inhibitory concentration (MIC) data.
Validate the results of an MIC experiment by comparing observed MIC values to
a gold standard assay, in line with standards from the International Organization for
Standardization (2021) <https://www.iso.org/standard/79377.html>. Perform MIC prediction from
whole genome sequence data stored in the Pathosystems Resource Integration Center (2013)
<doi:10.1093/nar/gkt1099> database or locally.

Alessandro Gerada

Analysis of Antimicrobial Minimum Inhibitory Concentration Data

droplevels.mic_validation function

<dl><dt>x</dt>
<dd>mic_validation object</dd>
<dt>safe</dt>
<dd>ensure that essential agreement is not changed after dropping
levels</dd>
<dt>...</dt>
<dd>additional arguments</dd></dl>

Arguments

Droplevels for MIC validation object — droplevels.mic_validation

<dl>

<dt>x</dt>
<dd>mic_validation object</dd>


<dt>safe</dt>
<dd>ensure that essential agreement is not changed after dropping
levels</dd>


<dt>...</dt>
<dd>additional arguments</dd>

</dl>

droplevels.mic_validation: Droplevels for MIC validation object

Description

Usage

Value

Arguments

Examples