<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-statistics-and-management-systems</journal-id>
      <journal-title-group>
        <journal-title> Journal of Statistics and Management Systems</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0014</issn>
      <issn publication-format="print">0972-0510</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JSMS-1024</article-id>
      <title-group>
        <article-title>ShinySurv : A survival analysis and Shiny web application</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Sağlam</surname>
            <given-names>Fatih</given-names>
          </name>
          <aff>Department of Statistics, Faculty of Art and Sciences, Ondokuz Mayis University, Samsun, 55270, Turkey</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Şanlı</surname>
            <given-names>Tuba</given-names>
          </name>
          <aff>Department of Finance and Banking, Görele School of Applied Sciences, Giresun University, Giresun, 28800, Turkey</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cengiz</surname>
            <given-names>Mehmet Ali</given-names>
          </name>
          <aff>Department of Statistics, Faculty of Art and Sciences, Ondokuz Mayis University, Samsun, 55270, Turkey</aff>
        </contrib>
      </contrib-group>
      <volume>27</volume>
      <issue>8</issue>
      <fpage>1557</fpage>
      <lpage>1575</lpage>
      <pub-date date-type="pub">
        <day>18</day>
        <month>12</month>
        <year>2024</year>
      </pub-date>
      <abstract>
        <p>There are different programs available for survival analysis. However, these programs do not deal with survival problems with all censor types. The aim of this study is to form and explain “ShinySurv” application of survival analysis methods in R-Shiny for different types of censorship. Using ShinySurv, the user can upload his own data set to the system or benefit from sample data sets. ShinySurv provides visualization of analysis results with graphs and reporting of results for parametric and non-parametric survival methods. An example application of a survival analysis is given. The web application and the codes can be accessed at https://scypter.shinyapps.io/ShinySurv/ and https://github.com/fatihsaglam/ShinySurv.</p>
      </abstract>
      <kwd-group>
        <kwd>Shiny</kwd>
        <kwd>Web application</kwd>
        <kwd>Survival analysis</kwd>
        <kwd>Censored data</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
