
<?xml version='1.0' encoding='UTF-8'?>
<article>
<front>
<journal-meta>
<journal-id journal-id-type='publisher'>IJRAP</journal-id>
<journal-title>International Journal of Research in Ayurveda and Pharmacy</journal-title>
<issn pub-type='ppub'>2277-4343</issn>
 <publisher>
<publisher-name>Moksha Publishing House </publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type='other'>10.7897/2277-4343.130374</article-id>
<title-group>
<article-title>RECEIVER OPERATING CHARACTERISTIC CURVE ANALYSIS IN DIAGNOSTIC RESEARCH: A REVIEW
</article-title>
</title-group>
<contrib-group>
<contrib contrib-type='author'>
<name>Kalesh M Karun</name>
</contrib>
<contrib contrib-type='author'>
<name> Amitha Puranik *</name>
</contrib>
</contrib-group>
<pub-date>
<month>11</month>
<year>-0001</year>
</pub-date>
<fpage>132</fpage>
<lpage>133</lpage>
<abstract><title>Abstract</title>
Optimal dose selection in clinical trials is problematic when efficacious and toxic concentrations are close. A receiver operating characteristic curve is a graphical technique used to identify the optimal cut-off point for a continuous variable. Implementation of ROC analysis is currently possible using various statistical software packages. However, the process is straightforward in the EZR package of R software. This present study aims to provide a tutorial using a simple example and a detailed description of the procedure in EZR software. The information provided can help the researchers perform the analysis independently.
</abstract>
<kwd-group>
<title>Keywords</title>
<kwd>ROC curve</kwd>
<kwd> diagnostic test</kwd>
<kwd> sensitivity</kwd>
<kwd> specificity</kwd>
</kwd-group>
<counts><ref-count count='56635'/><page-count count='80'/></counts>
</article-meta></front><back><ref-list><title>References</title></ref-list></back></article>
