Showing items related by title, author, creator and subject.

• Use of instrumental variable in prescription drug research with observational data: a systematic review

  Chen, Yong; Briesacher, Becky A. (2011-06-14)

  OBJECTIVE: Instrumental variable (IV) analysis may offer a useful approach to the problem of unmeasured confounding in prescription drug research if the IV is: (1) strongly and unbiasedly associated to treatment assignment; and (2) uncorrelated with factors predicting the outcome (key assumptions). STUDY DESIGN AND METHODS: We conducted a systematic review of the use of IV methods in prescription drug research to identify the major types of IVs and the evidence for meeting IV assumptions. We searched MEDLINE, OVID, PsychoInfo, EconLit, and economic databases from 1961 to 2009. RESULTS: We identified 26 studies. Most (n=16) were published after 2007. We identified five types of IVs: regional variation (n=8), facility-prescribing patterns (n=5), physician preference (n=8), patient history/financial status (n=3), and calendar time (n=4). Evidence supporting the validity of IV was inconsistent. All studies addressed the first IV assumption; however, there was no standard for demonstrating that the IV sufficiently predicted treatment assignment. For the second assumption, 23 studies provided explicit argument that IV was uncorrelated with the outcome, and 16 supported argument with empirical evidence. CONCLUSIONS: Use of IV methods is increasing in prescription drug research. However, we did not find evidence of a dominant IV. Future research should develop standards for reporting the validity and strength of IV according to key assumptions.
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  Cohort Studies and Relative Risks

  Ssekitoleko, Richard (2019-02-01)

  This presentation provides an overview of cohort studies and relative risk. The learning objectives are to be able to: Define a cohort study and the steps for the study; Understand the populations in a cohort study; Understand timing in a cohort study and the difference between retrospective, prospective and ambi-directional cohort studies; Understand the selection of the cohort population and the collection of exposure and outcome data; Understand the sources of bias in a cohort study; Understand the calculation and interpretation of the relative risk; and, Understand use of the new-castle Ottawa quality assessment score for cohort studies.
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  Variables and Data Presentation

  Ssekitoleko, Richard (2018-11-01)

  This presentation provides an overview of the types of variables used in epidemiology. The learning objectives are to be able to: recognise different types of variables; and, explain how different types of variables are described, using graphs, using descriptive statistics, and to understand associations between variables.