Causal inference

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Causal inference is the process of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect. The main difference between causal inference and inference of association is that the former analyzes the response of the effect variable when the cause is changed.[1][2]

Common frameworks for causal inference are structural equation modeling and the Rubin causal model.

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References[edit]

  1. ^ Pearl, Judea (1 January 2009). "Causal inference in statistics: An overview". Statistics Surveys 3: 96–146. doi:10.1214/09-SS057. 
  2. ^ Morgan, Stephen; Winship, Chris (2007). Counterfactuals and Causal inference. Cambridge University Press. ISBN 978-0-521-67193-4.