rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Quantitative secondary data analysis
    sub title: utilizing observational studies for integrative neuroscience and interdisciplinary work
  name:
    name part: Webb, Joseph
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Wolf, Tovah
    role:
      role term: author.
  name:
    name part: Swanson, Ashley
    role:
      role term: author.
  name:
    name part: McLimans, Kelsey
    role:
      role term: author.
  name:
    name part: Klinedinst, Brandon
    role:
      role term: author.
  name:
    name part: Izbicki, Patricia
    role:
      role term: author.
  name:
    name part: Willette, Auriel A.
    role:
      role term: author.
  type of resource: text
  genre: Case studies.
  origin info:
    place:
      place term: xx
    place:
      place term: Place of publication not identified]
    publisher: Sage Publications Ltd
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: The National Institutes of Health and several other public and private agencies have funded longitudinal, observational studies to examine numerous mental and neurological disorders. There has been an increasing push by funding agencies for data to be readily available for use by any interested researcher in secondary data analysis. While there are several databases that are widely used and established, there are also many new, large datasets that are underutilized today. Integrated utilization of biological, behavioral, and brain data is an underdeveloped yet potentially fruitful enterprise. In particular, there is an increasing emphasis on the development of biomarkers to track the cause and development of neurological disorders. Furthermore, it is now possible to combine data across several datasets to answer novel questions of interest that would otherwise be difficult to study within one research institution or center. Such databases also allow researchers to investigate established topics with larger sample sizes, which minimizes spurious associations and enhances replicability. This case presents an approach to determining datasets of interest, logistics for combining data, and analysis considerations.
  note: Joseph Webb, Tovah Wolf, Ashley Swanson, Kelsey McLimans, Brandon Klinedinst, Patricia Izbicki & Auriel A. Willette.
  note: Title from content provider.
  subject:
    topic: Neurosciences
    topic: Research
    genre: Case studies
  subject:
    topic: Quantitative research
    topic: Research
    genre: Case studies
  subject:
    topic: Neurosciences
    topic: Recherche
    genre: Études de cas
  subject:
    topic: Recherche quantitative
    topic: Recherche
    genre: Études de cas
  subject:
    topic: Neurosciences
    topic: Research
  classification: RC343 .W43 2017
  classification: 616.8
  identifier: 9781473998100
  identifier: 1473998107
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: COO
    record creation date: 170209
    record change date: 20240923170215.6
    record identifier: in00005493388
    language of cataloging:
      language term: eng