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Abstract:
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 ....

United States , San Francisco , Maria Glymour , University Of California , School Of Medicine , Department Of Epidemiology Seminar Series , Epidemiology Seminar , ஒன்றுபட்டது மாநிலங்களில் , சான் பிரான்சிஸ்கோ , பல்கலைக்கழகம் ஆஃப் கலிஃபோர்னியா , பள்ளி ஆஃப் மருந்து , துறை ஆஃப் தொற்றுநோய் கருத்தரங்கு தொடர் , தொற்றுநோய் கருத்தரங்கு ,