Show simple item record

dc.contributor.authorKisely, Steve
dc.date.accessioned2021-09-06T06:25:07Z
dc.date.available2021-09-06T06:25:07Z
dc.date.issued2017
dc.identifier.issn0706-7437
dc.identifier.doi10.1177/0706743716660710
dc.identifier.urihttp://hdl.handle.net/10072/407675
dc.description.abstractA wide range of data sources are available to study the epidemiology of mental illness. Community surveys such as Alex Leighton’s Stirling County Study are the gold standard for such data sources, particularly because community surveys cover everyone, not just people seeking treatment. However, as surveys require a lot of resources, other methods are also used, each of which has strengths and weaknesses. For example, medical records contain detailed information, but this can be difficult to extract and the quality may vary. Another source entails administrative data, typically hospital separations, physician billings, ambulatory care visits, and drug databases. While such data require careful analysis with the use of multivariate or propensity score techniques to adjust for potential confounding variables, these data can be invaluable in the study of diseases with multifactorial aetiologies.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherSAGE Publications
dc.relation.ispartofpagefrom182
dc.relation.ispartofpageto185
dc.relation.ispartofissue3
dc.relation.ispartofjournalThe Canadian Journal of Psychiatry
dc.relation.ispartofvolume62
dc.subject.fieldofresearchBiomedical and clinical sciences
dc.subject.fieldofresearchPsychology
dc.subject.fieldofresearchcode32
dc.subject.fieldofresearchcode52
dc.subject.keywordsScience & Technology
dc.subject.keywordsLife Sciences & Biomedicine
dc.subject.keywordsPsychiatry
dc.subject.keywordsepidemiology
dc.subject.keywordssurveillance
dc.titleOn adjusting for life's confounding: Harnessing big data to answer big problems
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationKisely, S, On adjusting for life's confounding: Harnessing big data to answer big problems, The Canadian Journal of Psychiatry, 2017, 62 (3), pp. 182-185
dc.date.updated2021-09-06T06:23:38Z
gro.hasfulltextNo Full Text
gro.griffith.authorKisely, Steve R.


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record