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Causal Effect Estimation Methods
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0003-1654-9148
2014 (English)In: Journal of Statistical and Econometric Methods, ISSN 2241-0376, Vol. 3, no 2, 153-170 p.Article in journal (Refereed) Published
Abstract [en]

Relationship between two popular modeling frameworks of causalinference from observational data, namely, causal graphical model andpotential outcome causal model is discussed. How some popular causaleffect estimators found in applications of the potential outcome causalmodel, such as inverse probability of treatment weighted estimator anddoubly robust estimator can be obtained by using the causal graphicalmodel is shown. We confine to the simple case of binary outcome andtreatment variables with discrete confounders and it is shown how togeneralize results to cases of continuous variables.

Place, publisher, year, edition, pages
Scienpress Ltd , 2014. Vol. 3, no 2, 153-170 p.
Keyword [en]
Graphical models, potential outcomes, estimators
National Category
Probability Theory and Statistics
Research subject
URN: urn:nbn:se:umu:diva-88883OAI: diva2:717840
Swedish Research Council
Available from: 2014-05-18 Created: 2014-05-18 Last updated: 2014-05-19Bibliographically approved

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Wijayatunga, Priyantha
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