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Abstract Details
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Activity Number:
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128
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #302602 |
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Title:
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Achieving Covariate Balance in Factorial Designs Using the Finite Selection Model
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Author(s):
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Li Zhu*+ and Tirthankar Dasgupta
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Companies:
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Harvard University and Harvard University
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Address:
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Department of Statistics, Cambridge, MA, 02138,
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Keywords:
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Factorial Designs ;
Covariates ;
Finite Selection Model ;
Assignment Mechanism ;
Simulations
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Abstract:
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Factorial designs are widely used in agriculture, engineering and social sciences to study causal effects of several factors simultaneously on a response. Problems of application of factorial designs in social and medical experiments is the potential confounding of factorial effects with effects of a large number of covariates that are usually associated with the experimental units. Homogeneous groups of experimental units is therefore a challenge. In this research we explore an application of the Finite Selection Model (FSM) with the objective of allocating experimental units to different treatment groups so that the covariates are reasonably balanced across all factorial effects of interest. Theoretical properties of the design are established. Extensive simulation has demonstrated advantages of FSM method over traditional methods.
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