본문 바로가기
KERD
논문KCI 등재후보

여과 질문을 포함하는 설문조사의 항목무응답 대체방법 적용사례: 국민노후보장패널 자료를 이용하여

Imputation Methods for Item Non-Responses in Survey with Filter Variables: Application to Korean Retirement and Income Panel Survey

1

조회

0

다운로드

0

인용

0

참고문헌

초록

Objectives: For the analysis of survey data with filter questions, item-nonresponse can lead to se- rious bias. We consider appropriate imputation methods that can deal with item-nonresponses in fil- ter 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 impu- tation 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 imputa- tion 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.

Abstract

Objectives: For the analysis of survey data with filter questions, item-nonresponse can lead to se- rious bias. We consider appropriate imputation methods that can deal with item-nonresponses in fil- ter 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 impu- tation 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 imputa- tion 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.

참고문헌 (10)

  1. "Survey of Income and Program Participation (SIPP), 2014Panel Users’ Guide"[URL]
  2. Peracchi F, "The European community household panel : a review", Empir Econ, 27, pp.63~90 (2002)
  3. "Naional Health Interview Survey"[URL]
  4. "KReIS: Korean Retirement and Income Study"[URL]
  5. National Pension Research Institute, "Korean Retirement and Income Study Users’ Guide. Ver.3.6", ~ (2011)
  6. Rubin DB, "Multiple imputation for nonresponse in surveys. Vol. 81" (2004), John Wiley & Sons
  7. IVEware: Imputation and variance estimation software, "Raghunathan TE", Survey Methodology Program, Survey Research Center, Institute for Social Research, University of Michigan, ~ (2002)
  8. Raghunathan TE, "A multivariate technique for multiply imputing missing values using a sequence of regression models", Surv Methodol, 27, pp.85~96 (2001)
  9. Carlson BL, "SAS macros useful in imputing missing survey data", Proceedings of the Twentieth Annual SAS Users’ Group International Conference, pp.1089~1094 (1995), Mathematica Policy Research, Inc
  10. "Multiple imputation in a complex household surveythe German Panel on Household Finances (PHF): challenges and solutions"[URL]

관련 논문AI추천

이 간행물의 다른 논문 (6건)