The Annals of Applied Statistics

An imputation approach for handling mixed-mode surveys

Seunghwan Park, Jae Kwang Kim, and Sangun Park

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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.

Article information

Source
Ann. Appl. Stat., Volume 10, Number 2 (2016), 1063-1085.

Dates
Received: July 2014
Revised: March 2016
First available in Project Euclid: 22 July 2016

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1469199905

Digital Object Identifier
doi:10.1214/16-AOAS930

Mathematical Reviews number (MathSciNet)
MR3528372

Zentralblatt MATH identifier
06625681

Keywords
Counterfactual outcome fractional imputation measurement error model missing data survey sampling

Citation

Park, Seunghwan; Kim, Jae Kwang; Park, Sangun. An imputation approach for handling mixed-mode surveys. Ann. Appl. Stat. 10 (2016), no. 2, 1063--1085. doi:10.1214/16-AOAS930. https://projecteuclid.org/euclid.aoas/1469199905


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