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KMID : 1146320160040020067
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Journal of Health Technology Assessment
2016 Volume.4 No. 2 p.67 ~ p.74
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Imputation Methods for Item Non-Responses in Survey with Filter Variables: Application to Korean Retirement and Income Panel Survey
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Jee Hee-Jung
An Hyong-Gin
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Abstract
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Objectives: For the analysis of survey data with filter questions, item-nonresponse can lead to serious bias. We consider appropriate imputation methods that can deal with item-nonresponses in filter questions and evaluate the performance of the methods using real data analysis and simulation study.
Methods: In this paper, we considered two imputation methods, sequential regression imputation and sequential hot deck imputation, for the analysis of non-response survey data with filter questions. We reviewed these imputation methods and compare them with complete case analysis, available case analysis and mean imputation using real data set from Korean Retirement and Income Panel Study.
Results: Simulation results showed that two methods performed in similar way when the distributions of additional variables were relatively symmetric. When the distributions were very skewed, sequential hot deck imputation yielded robust results.
Conclusion: For the analysis of survey data with filter variables, item-nonresponse can lead to serious bias. Both suggested imputation methods seems to reduce bias. However, the sequential hot deck imputation method is more robust than the sequential regression imputation method. In other words, the sequential regression imputation method based on parametric model assumption is sensitive to model misspecification.
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KEYWORD
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Item-nonresponse, Filter question, Imputation, Panel data, Missing data
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