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Article
Integration of survey data and big observational data for finite population inference using mass imputation
arxiv
  • Shu Yang, North Carolina State University
  • Jae Kwang Kim, Iowa State University
Document Type
Article
Publication Version
Submitted Manuscript
Publication Date
7-8-2018
Abstract

Multiple data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we consider an imputation approach to combining a probability sample with big observational data. Unlike the usual imputation for missing data analysis, we create imputed values for the whole elements in the probability sample. Such mass imputation is attractive in the context of survey data integration (Kim and Rao, 2012). We extend mass imputation as a tool for data integration of survey data and big non-survey data. The mass imputation methods and their statistical properties are presented. The matching estimator of Rivers (2007) is also covered as a special case. Variance estimation with mass-imputed data is discussed. The simulation results demonstrate the proposed estimators outperform existing competitors in terms of robustness and efficiency.

Comments

This pre-print is made available through arxiv: https://arxiv.org/abs/1807.02817.

Copyright Owner
The Authors
Language
en
File Format
application/pdf
Citation Information
Shu Yang and Jae Kwang Kim. "Integration of survey data and big observational data for finite population inference using mass imputation" arxiv (2018)
Available at: http://works.bepress.com/jae-kwang-kim/47/