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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">030103</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.2005.03(1).196
</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Increasing the Precision of Estimates of Immunization Coverage Among 19- to 35-Month-Old Children in the United States</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Barker</surname>
            <given-names>Lawrence E.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Centers for Disease Control and Prevention</aff>
        <contrib contrib-type="author">
          <name>
            <surname>McCauley</surname>
            <given-names>Mary M.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Centers for Disease Control and Prevention</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Li</surname>
            <given-names>Qian</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">Centers for Disease Control and Prevention</aff>
      </contrib-group>
      <volume>3</volume>
      <issue>1</issue>
      <fpage>35</fpage>
      <lpage>45</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: The National Immunization Survey (NIS) is the United States’ primary tool for assessing immunization coverage among 19- to 35-monthold children. Although annual estimates from the NIS are quite precise at the national level, US State-level estimates have much larger sampling error than national-level estimates. We combined two independent unbiased estimates of US State-level coverages within a given year to obtain new estimates which are more precise than previously published estimates. We first calculated a model-based estimate for each State for 2001 using multiple years of NIS data. Next, we combined each model-based estimate with the corresponding, previously reported NIS estimate for 2001. Our resulting estimates of State-level immunization coverage had smaller standard errors than the previously published estimates. To make similar improvements in precision by increasing sample size would, depending on State, require an increase in sample size of 30% – 120%.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Epidemiologic methods</kwd>
        <kwd>immunization</kwd>
        <kwd>vaccination</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
