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Activity Number: 167 - SPEED: Missing Data and Causal Inference Methods, Part 1
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Health Policy Statistics Section
Abstract #301833 Presentation
Title: Using a Combination of Nearest Matching and Synthetic Control Methods in Causal Inference Study
Author(s): Zhiyiuan Dong*
Companies:
Keywords: causal inference; matching estimator; synthetic control methods
Abstract:

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.


Authors who are presenting talks have a * after their name.

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