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Activity Number: 241 - SPEED: Statistics in Social Sciences and Survey Research Part 1
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #323117
Title: Synthetic Data Generation for Complex Surveys
Author(s): Shirley Mathur* and Jerome P. Reiter
Companies: Duke University and Duke University
Keywords: confidentiality; disclosure; multiple imputation
Abstract:

Methodology for generating synthetic data has been developed mostly for data collected through censuses or simple random sample survey data. In practice, however, survey data often are collected via complex sampling designs. We present a multiple imputation based approach for generating the synthetic data in complex sampling designs. The basic idea is to create completed populations using bootstraps, take samples from these populations, and replace sensitive values with draws from statistical models. We also present inferential methods appropriate for analyzing such data.


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

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