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Activity Number: 154 - Some New Innovations in Survey Sampling and Missing Data Problems
Type: Topic-Contributed
Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
Sponsor: Survey Research Methods Section
Abstract #317568
Title: Multiply robust bootstrap procedure in the presence of imputed survey data
Author(s): Zeinab Mashreghi* and Sixia Chen and David Haziza
Companies: University of Winnipeg and University of Oklahoma Health Sciences Center and University of Ottawa
Keywords: Item Nonresponse; Multiply Robustness Property; Variance Estimation ; Complex Survey

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.

Authors who are presenting talks have a * after their name.

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