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Activity Number:
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177
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Type:
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Invited
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Date/Time:
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Monday, August 7, 2006 : 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 - #304939 |
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Title:
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Estimation of the Total Variance of Survey Statistics under Unweighted Imputation
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Author(s):
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Santanu Pramanik*+ and Partha Lahiri
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Companies:
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University of Maryland and University of Maryland
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Address:
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1218 Lefrak Hall, College Park, MD, 20742,
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Keywords:
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missing value ; imputation ; response propensity
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Abstract:
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In many complex surveys, unweighted imputation methods are employed because of the unavailability of survey weights at the time of imputing missing survey data. In such situations, it is well known that certain customary design-based estimators with imputed data generally are biased under the usual uniform response mechanism within each imputation cell and the sampling design. In this paper, we present the expression of the bias of a customary design-based estimator under ignorable response mechanism and then use this expression to propose a bias-corrected estimator. The second part of the paper deals with a variance estimator that captures different sources of uncertainties. Both theory and results from a Monte Carlo simulation study are presented to justify our approach.
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