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Activity Number:
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154
- Some New Innovations in Survey Sampling and Missing Data Problems
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Type:
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Topic-Contributed
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Survey Research Methods Section
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Abstract #317568
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Title:
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Multiply robust bootstrap procedure in the presence of imputed survey data
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Author(s):
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Zeinab Mashreghi* and Sixia Chen and David Haziza
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Companies:
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University of Winnipeg and University of Oklahoma Health Sciences Center and University of Ottawa
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Keywords:
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Item Nonresponse;
Multiply Robustness Property;
Variance Estimation ;
Complex Survey
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Abstract:
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Most surveys face the problem of item nonresponse which is usually dealt with some form of single imputation. It is well known that treating the imputed values as if they were observed values may lead to serious underestimation of the variance of point estimators. In this talk, three resampling bootstrap schemes under the pseudo-population bootstrap approach will be presented in order to estimate the variance of imputed estimators obtained after applying a multiply robust imputation procedure. The proposed multiply robust bootstrap procedures are capable of handling nonnegligible sampling fractions. To support our findings, some results from a simulation study will be presented.
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Authors who are presenting talks have a * after their name.
