응용통계연구 (The Korean Journal of Applied Statistics)

  • 제28권6호
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  • Pages.1217-1225
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  • 2015
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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설계효과모형을 통한 설계요소의 유용성 이해

Understanding Complex Design Features via Design Effect Models

  • Park, Inho (Department of Statistics, Pukyong National University)
  • 투고 : 2015.10.29
  • 심사 : 2015.11.13
  • 발행 : 2015.12.31
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초록

조사자료분석에 있어서 표본추정량에 대해 설계요소가 갖는 효율성은 단순확률추출과 비교한 복잡표본설계의 의한 표본추출이 주는 분산의 상대적 크기인 설계효과를 통해 평가할 수 있다. 설계효과의 유용성은 복잡설계요소의 함수형태로 표현될 수 있을때 극대화될 수 있다. 본 연구에서는 층화다단추출의 표본설계에서 적용될 수 있는 설계효과모형을 제시하였다. 제시된 설계효과모형은 기존 다단추출을 위한 Gabler 등 (1999, 2006)의 모형을 일반화한 것으로 층구조, 표본할당, 집락추출 및 불균등가중치 등의 설계요소들이 정도수준에 갖는 영향력을 함수식으로 명확히 나타내주고 있다. 이를 활용하면 사전에 기술된 추정정도를 얻기 위해 설정한 표본크기가 줄 수 있는 설계효과를 예측하는데 활용할 수 있다. 또한 사후적으로 표본설계의 개별 설계요소들이 표본추정량에 대해 갖는 효율성을 평가하는데 활용될 수 있다.

Survey research, data is commonly collected through a sample design with complex design features that allow the relative efficiency on the precision of an estimator to be measured using the concept of the design effect compared to simple random sampling as a reference design. This concept is most useful when the design effect can be expressed as a function of various design features. We propose a design effect formula suitable under a stratified multistage sampling by generalizing Gabler et al. (1999, 2006)'s approaches for multistage sampling. Its use can either guide improvement in the design efficiency when in design stage or enable the evaluation of the adopted design features afterwards.

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참고문헌

  1. Cornfield, J. (1951). Modern methods in the sampling of human populations, American Journal of Public Health, 41, 654-661. https://doi.org/10.2105/AJPH.41.6.654
  2. Gabler, S., Ganninger, M. and Lahiri, P. (2014). A new approximation to the true randomization-based design effect, Submitted to a journal.
  3. Gabler, S., Hader, S. and Lahiri, P. (1999). A Model based justification of Kish's formula for design effects for weighting and clustering, Survey Methodology, 25, 105-106.
  4. Gabler, S., Hader, S. and Lynn, P. (2006). Design effects for multiple design samples, Survey Methodology, 32, 115-120.
  5. Henry, K. A. (2011). Weighting adjustment methods and their impact on sample-based inference (Ph.D. thesis), University of Maryland, College Park, MD.
  6. Holt, D. (1980). Discussion of the paper by Verma, Scott, and O'Muircheartaigh, Journal of Royal Statistical Society-A, 143, 468-469.
  7. Jabkowski, P. (2013). How (not) to estimate the design effect of a complex sampling scheme: a case study of the Polish section of the European social survey, round 5, Ask Research & Methods, 22, 55-77.
  8. Kalton, G., Brick, J. M. and Le, T. (2005). Estimating components of design effects for use in sample design. In Household sample surveys in developing and transition countries,(Sales No. E.05.XVII.6). Department of Economic and Social Affairs, New York, Statistics Division, United Nations.
  9. Kish, L. (1965). Survey Sampling, John Wiley & Sons, New York.
  10. Kish, L. (1987). Weighting in Deft2, Survey Statistician, 26-30.
  11. Kish, L. (1992). Weighting for unequal pi, Journal of Official Statistics, 8, 183-200.
  12. Korn, E. L. and Graubard, B. I. (1999). Analysis of Health Surveys, John Wiley & Sons, New York.
  13. Le, T., Brick, J. M. and Kalton, G. (2001). Decomposing design effects, In Proceedings of the Joint Statistical Meetings, Section on Survey Research Methods, American Statistician Association, CD-Rom.
  14. Lee, H. (2012). How should one find out the contributions to the design effect (variance) made by each of the design components (stratification, clustering, weighting) of a complex sample design?, Survey Statistician, 66, 16-20.
  15. Park, I. (2014). A study on design effect models for complex sample survey, Journal of the Korean Data & Science Society, 25, 523-531.
  16. Park, I. (2015). Assessing complex sample designs via design effect decompositions, Submitted to a journal.
  17. Park, I. and Lee, H. (2004). Design effects for the weighted mean and total estimators under complex survey sampling, Survey Methodology, 30, 183-193.
  18. Rao, J. N. K. and Scott, A. J. (1987). On simple adjustments to chi-square tests with sample survey data, Annals of Statistics, 15, 385-397. https://doi.org/10.1214/aos/1176350273
  19. Rust, K. and Broene, P. (2010). Design effects for totals in multi-stage samples, Proceedings of the Joint Statistical Meetings, Section on Survey Research Methods, American Statistician Association, 2174-2181.
  20. Spencer, B. D. (2000). An approximate design effect for unequal weighting when measurements may correlate with selection probabilitie, Survey Methodology, 26, 137-138.
  21. Verma, V., Scott, C. and O'Muircheartaigh, C. (1980). Sample designs and sampling errors for the World Fertility Survey, Journal of Royal Statistical Society-A, 143, 431-473. https://doi.org/10.2307/2982064