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Activity Number:
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402
- Integrative Inference with Data from Multiple Sources: Challenges and New Developments
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Type:
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Topic-Contributed
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Date/Time:
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Thursday, August 12, 2021 : 2:00 PM to 3:50 PM
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Sponsor:
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ENAR
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Abstract #317043
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Title:
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Data Integration with Oracle Use of External Information from Heterogeneous Populations
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Author(s):
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Peisong Han*
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Companies:
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University of Michigan
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Keywords:
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Abstract:
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It is common to have access to auxiliary information from external studies. Such information can be useful in model building for an internal study of interest and can improve parameter estimation efficiency when incorporated. However, external studies may target populations different from the internal study population, in which case an incorporation of the corresponding information may introduce estimation bias. We develop a method that selects the external studies whose target population is the same as the internal study and simultaneously incorporates their available information into estimation. The resulting estimator has the efficiency as if we knew which external studies target the same population and made use of information from those studies alone.
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Authors who are presenting talks have a * after their name.
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