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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">040307</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.2006.04(3).275
</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Critical Values and Power for a Small Sample Test of Difference in Proportions in the Presence of Extra-Binomial Variation</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Lawson</surname>
            <given-names>John S.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Brigham Young University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Ahlstrom</surname>
            <given-names>Benjamin</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Bandag Inc</aff>
      </contrib-group>
      <volume>4</volume>
      <issue>3</issue>
      <fpage>357</fpage>
      <lpage>370</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: We develop a likelihood ratio test statistic, based on the betabinomial distribution, for comparing a single treated group with dichotomous data to dual control groups. This statistic is useful in cases where there is overdispersion or extra-binomial variation. We apply the statistic to data from a two year rodent carcinogenicity study with dual control groups. The test statistic we developed is similar to others that have been developed for incorporation of historical control groups with rodent carcinogenicity experiments. However, for the small sample case we considered, large sample theory used by the other test statistics did not apply. We determined the critical values of this statistic by enumerating its distribution. A small Monte Carlo study shows the new test statistic controls the significance level much better than Fisher’s exact test when there is overdispersion and that it has adequate power.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Beta-binomial distribution</kwd>
        <kwd>dual control groups</kwd>
        <kwd>historical controls</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
