| Inference for influence over multiple degrees of separation on a social network. | |
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MedLine Citation:
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PMID: 23341081 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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States and behaviors of different individuals are expected to be correlated across a social network. Christakis and Fowler have proposed a 'three degrees of influence rule' to characterize the extent of such dependence. In this paper, we discuss three distinct interpretations of such a rule, one involving only associations (which is the interpretation for which Christakis and Fowler give evidence), one involving actual causation, generally referred to as contagion or social influence, and one involving direct effects. We discuss analytic procedures appropriate for assessing evidence for each possible interpretation and the increasingly difficult methodological challenges present in each interpretation. Copyright © 2012 John Wiley & Sons, Ltd. |
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Authors:
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Tyler J Vanderweele |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Statistics in medicine Volume: 32 ISSN: 1097-0258 ISO Abbreviation: Stat Med Publication Date: 2013 Feb |
Date Detail:
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Created Date: 2013-01-23 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: England |
Other Details:
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Languages: eng Pagination: 591-6 Citation Subset: IM |
Copyright Information:
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Copyright © 2012 John Wiley & Sons, Ltd. |
Affiliation:
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Department of Epidemiology, Harvard School of Public Health, Boston, MA, U.S.A.; Department of Biostatistics, Harvard School of Public Health, Boston, MA, U.S.A. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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