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Activity Number:
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419
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #303572 |
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Title:
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Robustness of Efficiency in Semiparametric Models for Incomplete Data
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Author(s):
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Thomas Lumley*+
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Companies:
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University of Washington
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Address:
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Dept of Biostatistics, Seattle, WA, 98195-7232,
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Keywords:
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case-only ; calibration ; AIPW ; two-phase ; misspecification
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Abstract:
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An interaction term between two binary exposures in a logistic regression model can be estimated by case-control logistic regression. If the two exposures are known to be independent, the same interaction term can also be estimated more efficiently by a case-only analysis. Unfortunately, the case-only analysis loses its efficiency advantage under small departures from independence that cannot reliably be diagnosed from the data. The same phenomenon occurs generally when comparing estimators based on sampling weights with the semiparametric efficient estimator in regression models for incomplete data. The semiparametric efficient estimator, which is more efficient when the model is correctly specified, loses its efficiency advantage under misspecification that cannot be reliably detected even by the Neyman-Pearson type test.
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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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