A new document has been added to the Society for Political Methodology Website.

 Title:     A Unified Approach to Generalized Causal Inference

Author(s):     Fernando Martel Garcia

Entry Date:     2013-08-01

Keyword(s):     External validity, causal diagrams, dags, generalizability, experiments, learning

Abstract:      Randomized controlled trials and natural experiments have been criticized for their lack of generalizability (external validity), questioning their usefulness to social science and policy. Here I show how three common approaches to generalizability - the heuristic, statistical, and structural approaches --, are each incomplete on their own, and how generalized causal diagrams, or g-dags, can achieve a complete representation of the problem. G-dags combine theory and evidence to (1) make inferences from a study to a population, or subgroup; (2) combine two or more studies that are not generalizable on their own, into a generalized inference; (3) encode and test generalizable knowledge; and (4) provide a link to boosting algorithms as generalized additive models. Just as important, g-dags make make explicit what is being assumed, or questioned, in discussing the generalizability of experiments. This allows for constructive discourse and informed research agendas.
 

http://polmeth.wustl.edu/mediaDetail.php?docId=1425

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