Pub. date: 2008 | Online Pub. Date: November 27, 2007 | DOI: 10.4135/9781412953948 | Print ISBN: 9781412928168 | Online ISBN: 9781412953948| Publisher:SAGE Publications, Inc.About this encyclopedia
Causation and Causal Inference
In the health sciences, definitions of cause and effect have not been tightly bound with methods for studying causation. Indeed, many approaches to causal inference provide no definition, leaving users to imagine causality however they prefer. Without a formal definition of causation, an association is distinguished as causal only by having been identified as such based on external and largely contextual considerations. Because they have historical precedence and are still widely used, this entry first reviews such methods. It then discusses definitions and methods based on formal models of causation, especially those based on counterfactuals or potential outcomes. The oldest and most common systematic approach to causal inference in epidemiology was the comparison of observations to characteristics expected of causal relations. The characteristics might derive from subject-matter judgments or from consideration of causal models, and the comparisons might employ formal statistical methods to estimate and test those characteristics. Perhaps the ...