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  <titleInfo>
    <title>Meta-analysis, decision analysis, and cost-effectiveness analysis</title>
    <subTitle>methods for quantitative synthesis in medicine</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Petitti, Diana B.</namePart>
    <role>
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    <place>
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    <place>
      <placeTerm type="text">Oxford</placeTerm>
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    <publisher>Oxford University Press</publisher>
    <dateIssued>c2000</dateIssued>
    <dateIssued encoding="marc">2000</dateIssued>
    <edition>2nd ed.</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>1 online resource (x, 306 p.) : ill.</extent>
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  <abstract>In this 2nd edition Petitti has added new material on cumulative meta-analysis and the exploration of heterogeneity, incorporated recommendations for standardizing the conduct of cost-effectiveness analysis, and updated the rest of the text.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Diana B. Petitti.</note>
  <note>Previous ed.: 1994.</note>
  <note>Includes bibliographical references and index.</note>
  <subject authority="lcsh">
    <topic>Medicine</topic>
    <topic>Decision making</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Statistical decision</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Meta-analysis</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Cost effectiveness</topic>
  </subject>
  <classification authority="lcc">R723.5 .P48 2000</classification>
  <classification authority="ddc" edition="22">614.4072</classification>
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    <titleInfo>
      <title>Monographs in epidemiology and biostatistics ; v. 31</title>
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  <identifier type="isbn">9780199863761 (ebook) :</identifier>
  <identifier type="uri">http://dx.doi.org/10.1093/acprof:oso/9780195133646.001.0001</identifier>
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    <url displayLabel="Oxford scholarship online">http://dx.doi.org/10.1093/acprof:oso/9780195133646.001.0001</url>
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