Misunderstandings between Experimentalists and Observationalists about Causal Inference

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Misunderstandings between Experimentalists and Observationalists about Causal Inference

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Title: Misunderstandings between Experimentalists and Observationalists about Causal Inference
Author: Imai, Kosuke; King, Gary; Stuart, Elizabeth

Note: Order does not necessarily reflect citation order of authors.

Citation: Imai, Kosuke, Gary King, and Elizabeth Stuart. 2008. Misunderstandings between experimentalists and observationalists about causal inference. Journal of the Royal Statistical Society Series A 171(2): 481-502.
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Abstract: We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fallacies of causal inference. These issues concern some of the most fundamental advantages and disadvantages of each basic research design. Problems include improper use of hypothesis tests for covariate balance between the treated and control groups, and the consequences of using randomization, blocking before randomization and matching after assignment of treatment to achieve covariate balance. Applied researchers in a wide range of scientific disciplines seem to fall prey to one or more of these fallacies and as a result make suboptimal design or analysis choices. To clarify these points, we derive a new four-part decomposition of the key estimation errors in making causal inferences. We then show how this decomposition can help scholars from different experimental and observational research traditions to understand better each other's inferential problems and attempted solutions.
Published Version: doi:10.1111/j.1467-985X.2007.00527.x
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4142695

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  • FAS Scholarly Articles [6463]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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