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Community Health Sciences - University of Manitoba

Henry’s research will investigate outlier detection methods and tools, including visualization techniques, for meta-analyses, in which effect sizes (such as odds ratios or hazard ratios) from individual studies are combined to produce an overall (i.e., average) effect size. His work will benefit the Canadian Network of Observational Drug Effect Studies (CNODES), which conducts drug safety and effectiveness studies using administrative healthcare data. Henry’s research interests also include communicable and non-communicable diseases, and maternal and child health with the methodologies in meta-analyses, survival-analyses, machine learning, and generalized linear regression modeling. YOu can learn more through his ResearchGate profile

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