June 17, 2019 Lesson Open Access

Luke W Johnston

DataCite XML Export

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  <identifier identifierType="DOI">10.5281/zenodo.3247819</identifier>
  <creators>
    <creator>
      <creatorName>Luke W Johnston</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-4169-2616</nameIdentifier>
      <affiliation>Aarhus University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>acdcourse: Analyzing Cohort Datasets with R</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>cohort studies</subject>
    <subject>data analysis</subject>
    <subject>health sciences</subject>
    <subject>R</subject>
    <subject>Interactive tutorials</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-06-17</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="InteractiveResource"/>
  <alternateIdentifiers>
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  </relatedIdentifiers>
  <version>v0.1.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;&lt;strong&gt;Interactive tutorials on analyzing cohort datasets: First release!&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Cohort studies are a powerful study design that allows researchers to better understand how to reduce, manage, or prevent disease in a population. In this course, we&amp;#39;ll be covering how and what to analytically ask of cohort data, what are special considerations for data processing, which statistical techniques to choose, and how to present the results for effective communication to public health professionals.&lt;/p&gt;</description>
  </descriptions>
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