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Likelihood analysis of the binary instrumental variable model

Abstract:

Instrumental variables are widely used for the identification of the causal effect of one random variable on another under unobserved confounding. The distribution of the observable variables for a discrete instrumental variable model satisfies certain inequalities but no conditional independence relations. Such models are usually tested by checking whether the relative frequency estimators of the parameters satisfy the constraints. This ignores sampling uncertainty in the data. Using the obs...

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Publication status:
Published

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Publisher copy:
10.1093/biomet/asr040

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
BIOMETRIKA
Volume:
98
Issue:
4
Pages:
987-994
Publication date:
2011-12-01
DOI:
EISSN:
1464-3510
ISSN:
0006-3444
Source identifiers:
216533
Language:
English
Keywords:
Pubs id:
pubs:216533
UUID:
uuid:b274ae89-701b-4b19-9c25-fb2ec9aeafef
Local pid:
pubs:216533
Deposit date:
2012-12-19

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