Helps a clinical trial team  discuss
the clinical goals  of a well-defined biomarker with a diagnostic,
staging, prognostic, or predictive purpose.  From this discussion will
come a statistical plan for a (non-randomized) validation trial.
Both prospective and retrospective trials are supported. In a specific
focused discussion, investigators should determine the range of
"discomfort" for the NNT, number needed to treat.  The meaning of
the discomfort range, [NNTlower, NNTupper], is that within this range
most physicians would feel discomfort either in treating or withholding
treatment. A pair of NNT values bracketing that range, NNTpos and NNTneg,
become the targets of the study's design.  If the trial can demonstrate
that a positive biomarker test yields an NNT less than NNTlower,
and that a negative biomarker test yields an NNT less than NNTlower,
then the biomarker may be useful for patients. A highlight of the package
is visualization of a "contra-Bayes" theorem, which produces criteria for
retrospective case-controls studies.

Calculate Design Parameters for Biomarker Validation Studies

package-ubuntu-20.04-r-4.0.5#cran#NNTbiomarker-0.29.11

Computes sensitivity and specificity from predictive values.

sesp.from.pv(ppv = 0.1, npv = 0.7, pv, prev = 0.2)

<table summary="R argblock">
<tr valign="top">
<td><code>ppv</code></td>
<td>
Positive predictive value
</td>
</tr>
<tr valign="top">
<td><code>npv</code></td>
<td>
Negative predictive value
</td>
</tr>
<tr valign="top">
<td><code>pv</code></td>
<td>
Alternative input of ppv and npv, in matrix or named vector.
</td>
</tr>
<tr valign="top">
<td><code>prev</code></td>
<td>
Prevalence (prior probability)
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#NNTbiomarker-0.29.11#docs#sesp.from.pv

sesp.from.pv

Description

Usage

Arguments

Value

NNTbiomarker

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`ppv`	Positive predictive value
`npv`	Negative predictive value
`pv`	Alternative input of ppv and npv, in matrix or named vector.
`prev`	Prevalence (prior probability)