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Article
An imputation approach for handling mixed-mode surveys
The Annals of Applied Statistics
  • Seunghwan Park, Seoul National University
  • Jae Kwang Kim, Iowa State University
  • Sangun Park, Yonsei University
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2016
DOI
10.1214/16-AOAS930
Abstract

Mixed-mode surveys are becoming more popular recently because of their convenience for users, but different mode effects can complicate the comparability of the survey results. Motivated by the Private Education Expenditure Survey (PEES) of Korea, we propose a novel application of fractional imputation to handle mixed-mode survey data. The proposed method is applied to create imputed values of the unobserved counterfactual outcome variables in the mixed-mode surveys. The proposed method is directly applicable when the choice of survey mode is self-selected. Variance estimation using Taylor linearization is developed. Results from a limited simulation study are also presented.

Comments

This article is published as Park, Seunghwan, Jae Kwang Kim, and Sangun Park. "An imputation approach for handling mixed-mode surveys." The Annals of Applied Statistics 10, no. 2 (2016): 1063-1085. doi:10.1214/16-AOAS930. Posted with permission.

Copyright Owner
Institute of Mathematical Statistics
Language
en
File Format
application/pdf
Citation Information
Seunghwan Park, Jae Kwang Kim and Sangun Park. "An imputation approach for handling mixed-mode surveys" The Annals of Applied Statistics Vol. 10 Iss. 2 (2016) p. 1063 - 1085
Available at: http://works.bepress.com/jae-kwang-kim/9/