12-Confounding

12-Confounding - Confounding 1 Confounding Principles of Epidemiology for Public Health(EPID600 Victor J Schoenbach PhD www.unc.edu/~vschoenb

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Unformatted text preview: 4/5/2011 Confounding 1 Confounding Principles of Epidemiology for Public Health (EPID600) Victor J. Schoenbach, PhD www.unc.edu/~vschoenb/ Department of Epidemiology Gillings School of Global Public Health University of North Carolina at Chapel Hill www.unc.edu/epid600/ “Brain Cramps” "interesting" comments by well-known people (Received from Natasha Jamison, EPID160 graduate) That’s what can be further from the truth! “I was provided with additional input that was radically different from the truth. I assisted in furthering that version.” – Colonel Oliver North, from his Iran-Contra testimony. Equal opportunity employer “We don't necessarily discriminate. We simply exclude certain types of people.” – Colonel Gerald Wellman, ROTC Instructor. Quite a high risk, I’d say “If we don't succeed, we run the risk of failure.” – President Bill Clinton Why I’m glad no one is taping me “We are ready for an unforeseen event that may or may not occur.” – Vice President Al Gore Confounding 7 We are here • [Now leaving] Sources of error Confounding • [Now entering] Data analysis and interpretation Causal inference Confounding 8 Setting the scene “The data speak for themselves.” versus “Our data say nothing at all.” (Epidemiology guru Sander Greenland, Congress of Epidemiology 2001, Toronto) Confounding 9 Setting the scene • Logically sound inferences involve (1) data + (2) assumptions • No assumptions no inference • So always need a conceptual model Sander Greenland, Congress of Epidemiology 2001, Toronto Confounding 10 Causal inference in everyday living Does exercise make me feel better? • Try getting exercise – how do I feel? • Try not getting exercise – how do I feel? • Try getting exercise again – do I feel better? Confounding 11 Causal inference in everyday living Does getting too little sleep make me irritable? • Try sleeping too little – ask my partner • Try sleeping enough – ask my partner • Try sleeping too little – ask my partner Confounding 12 Desirable attributes of crossover experiments • Exposure is under investigator’s control • Comparison condition is a true control • Can go back and forth, providing some control for secular changes Confounding 13 Constraints on cross-over experiments • Exposures may be harmful or not under our control • Effects may not be quickly reversible • Experimental subjects or the environment may have changed Confounding 14 Key attribute of crossover experiments Can compare what happens to people who are exposed to what happens to the same people when they are not exposed – almost at the same time Confounding 15 People...
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This note was uploaded on 02/13/2012 for the course EPID 600 taught by Professor Staff during the Spring '08 term at UNC.

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12-Confounding - Confounding 1 Confounding Principles of Epidemiology for Public Health(EPID600 Victor J Schoenbach PhD www.unc.edu/~vschoenb

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