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Activity Number:
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160
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Type:
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Roundtables
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Date/Time:
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Monday, July 30, 2007 : 12:30 PM to 1:50 PM
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Sponsor:
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Section on Health Policy Statistics
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| Abstract - #309165 |
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Title:
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Estimation of Causal Effects in Health Services and Outcome Research Using Observational Data
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Author(s):
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Lirong Zhao*+
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Companies:
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University of Maryland
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Address:
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220 Arch Street, Baltimore, MD, 21201,
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Keywords:
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propensity score ; instrumental variable
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Abstract:
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Sample selection bias is one of the major concerns in the estimation of causal effects using observational data in health services and outcome research when experimental designs are not feasible. Statisticians, epidemiologists, and econometricians have proposed many methods to adjust this bias over past decades. Propensity score (PS) and instrumental variable (IV) are two of the major methods that reduce the observable and unobservable biases, respectively. In this roundtable discussion, you will have the chance to share experiences of applications of these two methods in health policy statistics.
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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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