Epidemiology EPI202-01 Study Guide - Collinearity, Exchangeable Random Variables, Sensitivity Analysis
9 Feb 2014
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Document Summary
Research goal: compare 2 treatments with respect to a health or economic outcome. Counterfactual ideal: what is achievable is similar not same ; the best we can get is comparable treatment groups. Indication confounding by indication can be very strong. Subtype of indication if indication is very weak, subtype of indication could be strong. Severity of illness, concomitant illnesses, medications, contraindications/sensitivities. Implicit reasons: culture of medicalization, md training/experience, regional treatment patterns. Before an association can be interpreted as causal, one has to rule out chance, bias, and confounding. Confounding arises when people possess covariate patterns that are preferentially associated with a particular therapy or confer different baseline risks. Propensity adjustment seeks to balance covariate patterns between compared groups, and/or make it so that therapy users have the same baseline risk as non-users. Can adjust for confounding by measured confounders through restriction, stratification, matching, balancing, weighting (through standardization and iptw) and modeling, which are all amenable to propensity techniques!!
