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Abstract Details
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Activity Number:
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88
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #301951 |
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Title:
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Optimal Two-Phase Sampling Designs for Clustered Data
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Author(s):
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Michael A. McIsaac*+ and Richard J. Cook
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Companies:
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University of Waterloo and University of Waterloo
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Address:
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Department of Statistics and Actuarial Science, Waterloo, ON, N2L 3G1, Canada
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Keywords:
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Optimal sampling designs ;
Two-phase sampling ;
Incomplete Data ;
Missing covariates ;
Clustered responses
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Abstract:
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Two-phase sampling designs have been shown to increase efficiency in estimation of regression coefficients when responses are independently distributed given covariates. When data arise in clusters, however, optimal sampling schemes have been less studied. We derive optimal sampling criteria using joint selection models for units within a cluster in the case of an expensive covariate. The resultant efficiency gains are assessed in relation to sampling designs which ignore the within-cluster association. Attention is directed at the case of binary responses and analyses are considered based on both marginal methods using inverse weighted generalized estimating equations and likelihood methods.
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