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

Exact confidence intervals for a binomial proportion parameter.

binom.confint(k, n, alpha = 0.05, side = c("two", "upper", "lower"))

<table summary="R argblock">
<tr valign="top">
<td><code>k</code></td>
<td>
#"heads"
</td>
</tr>
<tr valign="top">
<td><code>n</code></td>
<td>
sample size
</td>
</tr>
<tr valign="top">
<td><code>alpha</code></td>
<td>
Confidence level
</td>
</tr>
<tr valign="top">
<td><code>side</code></td>
<td>
Sidedness of the hypothesis: c("two", "upper", "lower")
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#NNTbiomarker-0.29.11#docs#binom.confint

binom.confint

Description

Usage

Arguments

NNTbiomarker

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`k`	#"heads"
`n`	sample size
`alpha`	Confidence level
`side`	Sidedness of the hypothesis: c("two", "upper", "lower")