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Alzheimer’s Disease and Dementia: Learning More with Instrumental Variables-Inspired Approaches
February 3 @ 1:00 pm - 1:50 pm
Department of Epidemiology Seminar Series
Maria Glymour, ScD, MS
Professor, Epidemiology & Biostatistics
School of Medicine
University of California, San Francisco
Progress on research to prevent or treat Alzheimer’s disease and related causes of dementia (ADRD) has been disappointingly slow. The collection of diseases poses special difficulties for population research, including epidemiology. The predominant causal inference methods in epidemiology are based on fulfilling the ‘back-door criterion’, i.e., accounting for shared causes of exposure and outcome, are ill-matched for many problems in ADRD. Novel insights or more convincing findings may be derived when using methods based on instrumental variables (IV), i.e., identifying sources of variation in exposures of interest that are unrelated to the potential outcomes of ADRD. One major challenge in applying IV methods has been the need for large sample sizes, but this barrier is ameliorated as large data sets become commonplace. Another major challenge in applying IV methods is identifying plausible IVs, but because epidemiologists do not routinely use IV methods, they may not recognize potential IVs. I will discuss three examples of IV-inspired approaches in ADRD research, with the goal of stimulating discussion of other potential IVs.
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