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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">201701_1</article-id>
	  <article-id pub-id-type="doi">10.6339/JDS.201701_15(1).0001</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Assessing Agreement between Raters from the Point of Coefficients and Loglinear Models</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Yilmaz</surname>
            <given-names>Ayfer Ezgi</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Department of Statistics, Hacettepe University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Saracbasi</surname>
            <given-names>Tulay</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Department of Statistics, Hacettepe University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Saracbasi</surname>
            <given-names>Tulay</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">Department of Statistics, Hacettepe University</aff>
      </contrib-group>
      <volume>15</volume>
      <issue>1</issue>
      <fpage>1</fpage>
      <lpage>24</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>In square contingency tables, analysis of agreement between row and column classifications is of interest. For nominal categories, kappa co- efficient is used to summarize the degree of agreement between two raters. Numerous extensions and generalizations of kappa statistics have been pro- posed in the literature. In addition to the kappa coefficient, several authors use agreement in terms of log-linear models. This paper focuses on the approaches to study of interrater agreement for contingency tables with nominal or ordinal categories for multiraters. In this article, we present a detailed overview of agreement studies and illustrate use of the approaches in the evaluation agreement over three numerical examples.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Agreement</kwd>
        <kwd>kappa</kwd>
        <kwd>log-linear models</kwd>
        <kwd>multi-raters</kwd>
        <kwd>nominal</kwd>
        <kwd>or- dinal</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
