 Misunderstandings between experimentalists and observationalists about causal inferenceKosuke Imai, Gary King and Elizabeth A. Stuart Journal of the Royal Statistical Society Series A, 2008, vol. 171, issue 2, 481-502 Abstract: Summary. 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. Date: 2008 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:171:y:2008:i:2:p:481-502 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC. |
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