An imputation approach for handling mixed-mode surveys

Seunghwan Park, Jae Kwang Kim, Sangun Park

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1063-1085
Number of pages23
JournalAnnals of Applied Statistics
Volume10
Issue number2
DOIs
Publication statusPublished - 2016 Jun 1

Fingerprint

Mixed Mode
Imputation
Variance Estimation
Survey Data
Linearization
Fractional
Simulation Study
Education

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty

Cite this

Park, Seunghwan ; Kim, Jae Kwang ; Park, Sangun. / An imputation approach for handling mixed-mode surveys. In: Annals of Applied Statistics. 2016 ; Vol. 10, No. 2. pp. 1063-1085.
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An imputation approach for handling mixed-mode surveys. / Park, Seunghwan; Kim, Jae Kwang; Park, Sangun.

In: Annals of Applied Statistics, Vol. 10, No. 2, 01.06.2016, p. 1063-1085.

Research output: Contribution to journalArticle

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