DOI QR코드

DOI QR Code

Design-based and model-based Inferences in Survey Sampling

표본조사에서 설계기반추론과 모형기반추론

  • 김규성 (서울시립대학교 자연과학대학 통계학과)
  • Published : 2005.11.01

Abstract

We investigate both the design-based and model-based inferences, which are usual inferential methods in survey sampling. While the design-based inference is on the basis of randomization principle, The motel-based inference is based on likelihood principle as well as conditionality principle. There have been some disputes between two inferences for a long time and those have not yet been determined. In this paper we reviewed some issues on two inferences and compared their advantages and disadvantages in some viewpoints.

표본조사에서 이용하는 모수 추론 방법인 설계기반추론과 모형기반추론을 고찰하였다. 설계기반추론은 확률화 원리에 기초를 두고 있는 반면 모형기반추론은 가정한 모형에서 조건부 원리와 우도 원리에 바탕을 두고 있다. 두 추론은 서로 다른 이론적 근거를 사용하기 때문에 이론적 기초에 관한 논쟁이 오래 전부터 있어 왔으며 지금도 진행되고 있다. 이 논문에서는 두 추론 사이에 진행되었던 논쟁의 초점을 살펴보았고 몇 가지 관점에서 두 추론의 장단점을 비교하였다.

Keywords

References

  1. Bolfarine, H. and Zacks, S. (1992). Prediction Theory for Finite Populations, Springer-Verlag
  2. Basu, D. (1971). An essay on the logical foundations of survey sampling, part one, In: V.P. Godambc and D.A.Sprott (eds) Foundation of Statistical Inference, Holt, Rinehart and Winston. Toronto. 203-242
  3. Brewer, K.R.W. (1999). Design-based or prediction-based Inference? stratified random vs stratified balanced sampling, International Statistical Review, 67, 35-47 https://doi.org/10.1111/j.1751-5823.1999.tb00379.x
  4. Cassel, C.M., Sarndal, C.E. and Wretman, J.H. (1976). Some results on generalized difference estimation and generalized regression estimation for finite population, Biometrika, 63, 615-620 https://doi.org/10.1093/biomet/63.3.615
  5. Godambe, V.P. (1955). A unified theory of sampling from finite populations, Journal of the Royal Statistical Society, Ser. B 17, 269-278
  6. Godambe, V.P. (1966). A new approach to sampling from finite populations I & II, Journal of the Royal Statistical Society, Ser. B 28, 310-328
  7. Godambe, V.P. (1982). Estimation in survey sampling: robustness and optimality, Journal of the American Statistical Association, 77, 393-406 https://doi.org/10.2307/2287257
  8. Godambe, V.P. and Joshi, V.M. (1965). Admissibility and Bayes estimation in sampling finite populations I, Annals of Mathematical Statistics, 36, 1707-1722 https://doi.org/10.1214/aoms/1177699799
  9. Hansen, M.H., Madow, W.G. and Tepping. B.J. (1983). An evaluation of model- dependent and probability-sampling inferences in sample surveys, Journal of the American Statistical Association, 78, 776-807 https://doi.org/10.2307/2288182
  10. Iachan, R. (1984). Sampling strategies, robustness and efficiency: the state of art, International Statistical Review, 52, 209-218 https://doi.org/10.2307/1403103
  11. Isaki, C.T. and Fuller, W.A. (1982). Survey design under the regression superpopulation model, Journal of the American Statistical Association, 77, 89-9 https://doi.org/10.2307/2287773
  12. Neyman, J. (1934). On the different aspects of the representative method: the method of stratified sampling and the method of purposive selection, Journal of the Royal Statistical Society, Ser A 97, 558-625 https://doi.org/10.2307/2342192
  13. Royall, R.M. (1970). On finite population sampling theory under certain linear regression models, Biometrika, 57, 377-387 https://doi.org/10.1093/biomet/57.2.377
  14. Royall, R.M. (1971). Linear regression models in finite population sampling theory, In Foundation of Statistical Inference, Eds. V.P. Godambe & D.A. Sprott, 259-279. Toronto: Holt, Rinehert and Winston
  15. Royall, R.M. (1988). The prediction approach to sampling theory, Handbook of Statistics, 6, Sampling, 399-413. North-Holland
  16. Royall, R.M. and Cumberland, W.G. (1981). An empirical study of the ratio estimator and estimators of its variance, Journal of the American Statistical Association, 76, 66-88 https://doi.org/10.2307/2287043
  17. Smith, T.M.F. (1976). The foundation of survey sampling. Journal of the Royal Statistical Society, 139, 183-204 https://doi.org/10.2307/2345174
  18. Smith, T.M.F. (1984). Present position and potential developments, Journal of the Royal Statistical Society, 84, 208-221
  19. Thompsom, M.E. (1997). Theory of Sample Surveys, Chapman & Hall