Accounting for misclassification errors in observational studies using administrative databases

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Health services administrative databases have been widely used to assess risks associated with diseases and their treatments. Although these administrative databases are excellent sources of ready-to-use information on large number of patients at minimal costs, they are prone to measurement errors. Measurement errors can be due to case or exposure misclassification and can lead to erroneous results if not addressed properly in the study design and/or statistical analyses. My research program includes three projects, each addressing one aspect of measurement error.