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Abstract Details
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Activity Number:
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427
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #303287 |
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Title:
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Decomposing the Fraction of Missing Information Into Auxiliary Variable Contributions for Monitoring Survey Data
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Author(s):
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Rebecca Andridge*+
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Companies:
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The Ohio State University
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Address:
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B-116 Starling-Loving Hall, Columbus, OH, 43210,
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Keywords:
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Nonresponse ;
Auxiliary variable ;
Imputation
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Abstract:
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The fraction of missing information (FMI) has recently been proposed as an alternative to the response rate for monitoring the quality of survey data. In order for the FMI to inform data collection decisions (e.g., in adaptive designs or for future survey waves), it must be decomposed into the relative contributions of individual auxiliary variables. We investigate these relative contributions in two ways. First, under some simplifying assumptions, we analytically decompose FMI to show the impact of each covariate. Secondly, we discuss several methods for estimating these relative contributions to FMI in practice, and contrast with alternate quality indicators. The methods are illustrated using data from the National Health Interview Survey (NHIS).
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Authors who are presenting talks have a * after their name.
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