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Activity Number:
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9
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Type:
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Invited
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Date/Time:
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Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #307742 |
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Title:
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Propensity Score--Matching Design in Studies with Repeated Measures
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Author(s):
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Bo Lu*+
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Companies:
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The Ohio State University
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Address:
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B110 Starling-Loving Hall, SPH, Columbus, OH, 43235,
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Keywords:
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Observatioanl Studies ; Repeated Measures ; Propensity Scores ; Optimal Matching ; Non-bipartite Matching
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Abstract:
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In observational studies with repeated measures, treatment effects need to be clearly defined. To obtain unbiased the treatment effect estimation, with potentially time-dependent treatment and covariates, it is desirable to balance the distribution of the covariates at every time point. A propensity score based on the Cox proportional hazards model is proposed to incorporate the time dependent feature and implemented in risk set matching. Different optimal matching designs have been explored under different study setups. Simulation results and analysis of a practical example are presented.
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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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