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Activity Number:
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265
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Type:
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Invited
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Date/Time:
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Tuesday, July 31, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Council of Chapters
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| Abstract - #308055 |
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Title:
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Causal Inference as a Missing Data Problem: Past, Present, and Future
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Author(s):
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Donald B. Rubin*+
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Companies:
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Harvard University
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Address:
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Statistics Department, Cambridge, MA, 02138-2901,
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Keywords:
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Neyman-Rubin Model ; Missing data ; Potential outcomes
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Abstract:
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The problem of drawing inferences about causal effects has been conceptualized intuitively for many years as one of missing data, but has been formally treated this way only in the last century. The continuing development of this formalization has led to substantial insights into difficult problems, and it is anticipated that further insights will be forthcoming in the future. This presentation will give an idiosyncratic overview of this perspective.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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