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A Review of Causal Inference

In this report, I first review the evolution of ideas of causation as it relates to causal inference. Then I introduce two currently competing perspectives on this issue: the counterfactual perspective and the noncounterfactual perspective. The ideas of two statisticians, Donald B. Rubin, representing the counterfactual perspective, and A.P.Dawid, representing the noncounterfactual perspective are examined in detail and compared with the evolution of ideas of causality. The main difference between these two perspectives is that the counterfactual perspective is based on counterfactuals which cannot be observed even in principle but the noncounterfactual perspective only relies on observables. I describe the definition of causes and causal inference methods under both perspectives, and I illustrate the application of the two types of methods by specific examples. Finally, I explore various controversies on these two perspectives.

Identiferoai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1043
Date09 January 2009
CreatorsLIU, DAYANG
ContributorsJoseph D. Petruccelli, Advisor, Bogdan M. Vernescu, Department Head,
PublisherDigital WPI
Source SetsWorcester Polytechnic Institute
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses (All Theses, All Years)

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