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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.5
- 수록면
- 695 - 703 (9page)
- DOI
- 10.7465/jkdi.2021.32.3.695
이용수
초록· 키워드
오류제보하기
The exact combination of data collected from different objects is difficult. Data fusion is the statistical combination process of obtaining an integrated dataset using common variable. We consider three statistical techniques for data fusion: conditional mean matching using linear regression models, gamma regression using nonlinear regression models on two independent datasets, and a distance hot deck nonparametric approach based on the distance of each variable. The National Health Insurance Corporation"s National Health Screening Data are used to compare the performance of three models.
목차
Abstract
1. Introduction
2. Methods for data fusion
3. Data analysis
4. Concluding remarks
References
참고문헌 (12)
참고문헌 신청
D'Orazio, M. / 2006 / Statistical matching: theory and practice / Wiley
Kadane, J. B. / 1978 / Some statistical problems in merging data files. In Department of Treasury, Com-pendium of tax research / US Government Printing Office
Little, R. J. A. / 2002 / Statistical analysis with missing data / Wiley
Moriarity, C. / 2001 / Statistical matching : A paradigm for assessing the uncertainty in the procedure / Journal of Official Statistics 17:407~422
Moriarity, C. / 2003 / A note on Rubin's statistical matching using file concatenation with adjusted weights and multiple imputation / Journal of Business and Economic Statistics 21:65~73
Kadane, J. B. / 1978 / Some statistical problems in merging data files. In Department of Treasury, Com-pendium of tax research / US Government Printing Office
Little, R. J. A. / 2002 / Statistical analysis with missing data / Wiley
Moriarity, C. / 2001 / Statistical matching : A paradigm for assessing the uncertainty in the procedure / Journal of Official Statistics 17:407~422
Moriarity, C. / 2003 / A note on Rubin's statistical matching using file concatenation with adjusted weights and multiple imputation / Journal of Business and Economic Statistics 21:65~73
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