ppv.spatse

Diagnostic performance: Specificity from sensitivity, positive predictive value (PPV) and prevalence of the endpoint

Alternative and fast algorithms for the analysis of receiver operating
characteristics curves (ROC curves) as described in Thomas et al. (2017)
<doi:10.1186/s41512-017-0017-y> and Thomas et al. (2023) <doi:10.1016/j.ajogmf.2023.101110>.

Gregoire Thomas

alternativeROC

Alternative and Fast ROC Analysis

Robin Tuytten

Jef Moerman

Xavier Robin

Stefan Siegert

ppv.spatse function

<dl><dt>se</dt>
<dd>Sensitivity.</dd>
<dt>ppv</dt>
<dd>Positive predictive value.</dd>
<dt>prevalence</dt>
<dd>Prevalence of the endpoint in the study population.</dd></dl>

Arguments

Diagnostic performance: Specificity from sensitivity, PPV and prevalence — ppv.spatse

<dl>

<dt>se</dt>
<dd>Sensitivity.</dd>


<dt>ppv</dt>
<dd>Positive predictive value.</dd>


<dt>prevalence</dt>
<dd>Prevalence of the endpoint in the study population.</dd>

</dl>

ppv.spatse: Diagnostic performance: Specificity from sensitivity, PPV and prevalence

Description

Usage

Value

Arguments