Activity Number:
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167
- SPEED: Missing Data and Causal Inference Methods, Part 1
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Type:
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Contributed
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Date/Time:
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Monday, July 29, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #301833
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Presentation
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Title:
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Using a Combination of Nearest Matching and Synthetic Control Methods in Causal Inference Study
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Author(s):
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Zhiyiuan Dong*
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Companies:
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Keywords:
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causal inference;
matching estimator;
synthetic control methods
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Abstract:
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Matching Estimator ( Abadie and Imbens 2011 ) and Synthetic Control Methods ( Abadie, Diamond and Hainmueller 2010 ) are both useful methodologies conducting causal inference. This work will present empirical study results using a combination of these two methodologies in nearest distance matching settings where multiple categorical and continuous matching variables are involved. Various data-driven weight estimation methods will be applied in the weight estimation step of Synthetic Control Methods after K nearest distance control members are identified. Empirical study results using simulated data as well as example cross-sectional data sets in various published research will be presented and compared.
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Authors who are presenting talks have a * after their name.
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