On adjusting for life's confounding: Harnessing big data to answer big problems
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Abstract
A 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.
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The Canadian Journal of Psychiatry
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62
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3
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Biomedical and clinical sciences
Psychology
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Life Sciences & Biomedicine
Psychiatry
epidemiology
surveillance
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Kisely, 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