Week 6
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6. (10/10) Confounders & conditioning of analyses
Idea: Statistical associations between any two variables generally vary depending on the values taken by other "confounding" variables. We need to take this dependency (or conditionality) into account when using our analyses to make predictions or hypothesize about causes, but how do we decide which variables are relevant and real confounders?
Cases: Immunization levels, Premature mortality in Boston, Hormone replacement therapy (cont.), Birth weight and blood pressure, Control at work and mortality, Mendelian randomization to analyze environmental exposures
Readings: Egede 2003, Krieger 2005, Prentice 2005, Petitti 2005, Huxley 2002, Davies 2006, Davey-Smith 1997, Davey-Smith & Ebrahim 2007
Copyright ©2010 Peter Taylor, Ph.D.
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Peter Taylor.
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cchewadmin. (Jul 29, 2008). Week 6. Retrieved Nov 06, 2014, from UMass Boston OpenCourseware Web site: http://ocw.umb.edu/public-policy/epidemiological-thinking-for-non-specialists/schedule-links/week-6.
