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Activity Number:
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409
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #304039 |
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Title:
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Extensions of Proxy Pattern-Mixture Analysis for Survey Nonresponse
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Author(s):
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Rebecca Andridge*+ and Roderick J.A. Little
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Companies:
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University of Michigan and University of Michigan
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Address:
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1420 Washington Heights, Ann Arbor, MI, 48109,
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Keywords:
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Nonignorable nonresponse ; Nonresponse bias ; Missing data ; Survey data ; Bayesian methods
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Abstract:
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We consider assessment of nonresponse bias for the mean of a binary survey variable Y subject to nonresponse. We assume that there are a set of covariates observed for nonrespondents and respondents. To reduce dimensionality and for simplicity we reduce the covariates to a continuous proxy variable X that has the highest correlation with Y, estimated from a probit regression analysis of respondent data. We extend our previously proposed proxy-pattern mixture analysis for continuous outcomes to the binary outcome using a latent variable approach, applying a pattern-mixture model for the joint distribution of the proxy X and the underlying latent variable for the outcome Y. Methods are demonstrated through simulation and with data from the third National Health and Nutrition Examination Survey (NHANES III).
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