Sampling Error Estimation in Stratified Surveys
Affiliation(s)
Department of Mathematics, Campus de Elvi?a, University of A Coru?a, A Coru?a, Spain . Department of Mathematics, Campus de Elvi?a, University of A Coru?a, A Coru?a, Spain.
Department of Mathematics, Campus de Elvi?a, University of A Coru?a, A Coru?a, Spain . Department of Mathematics, Campus de Elvi?a, University of A Coru?a, A Coru?a, Spain.
ABSTRACT
Many operations carried out by official statistical institutes use
large-scale surveys obtained by stratified random sampling without replacement.
Variables commonly examined in this type of surveys are binary, categorical and
continuous, and hence, the estimates of interest involve estimates of
proportions, totals and means. The problem of approximating the sampling
relative error of this kind of estimates is studied in this paper. Some new
jackknife methods are proposed and compared with plug-in and bootstrap methods.
An extensive simulation study is carried out to compare the behavior of all the
methods considered in this paper.
Cite this paper
R. Cao, J. Vilar, J. Vilar and A. López, "Sampling Error Estimation in Stratified Surveys," Open Journal of Statistics, Vol. 3 No. 3, 2013, pp. 200-212. doi: 10.4236/ojs.2013.33023.
R. Cao, J. Vilar, J. Vilar and A. López, "Sampling Error Estimation in Stratified Surveys," Open Journal of Statistics, Vol. 3 No. 3, 2013, pp. 200-212. doi: 10.4236/ojs.2013.33023.
References
[1] S. K. Thompson, “Sampling,” Wiley, New York, 1992. [2] M. Quenouille, “Approximate Tests of Correlation in Time Series,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 11, No. 1, 1949, pp. 18-84. [3] B. Efron, “Bootstrap Methods: Another Look at the Jackknife,” The Annals of Statistics, Vol. 7, No. 1, 1979, pp. 1-26. doi:10.1214/aos/1176344552 [4] B. Efron, “The Jackknife, the Bootstrap, and Other Re sampling Plans, Siam Monograph 38,” Society of Indus trial and Applied Mathematics CBMS-NSF Monographs, 1982. [5] B. Efron and R. Tibshirani, “An Introduction to the Boot strap,” Chapman & Hall, New York, 1993. [6] P. J. Bickel and D. A. Freedman, “Asymptotic Normality and the Bootstrap in Stratified Sampling,” The Annals of Statistics, Vol. 12, No. 2, 1984, pp. 470-482. doi:10.1214/aos/1176346500 [7] J. G. Booth, R. W. Butler and P. Hall, “Bootstrap Methods for Finite Populations,” Journal of the American Statistical Association, Vol. 89, No. 248, 1994, pp. 1282-1289. doi:10.1080/01621459.1994.10476868
[1] S. K. Thompson, “Sampling,” Wiley, New York, 1992. [2] M. Quenouille, “Approximate Tests of Correlation in Time Series,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 11, No. 1, 1949, pp. 18-84. [3] B. Efron, “Bootstrap Methods: Another Look at the Jackknife,” The Annals of Statistics, Vol. 7, No. 1, 1979, pp. 1-26. doi:10.1214/aos/1176344552 [4] B. Efron, “The Jackknife, the Bootstrap, and Other Re sampling Plans, Siam Monograph 38,” Society of Indus trial and Applied Mathematics CBMS-NSF Monographs, 1982. [5] B. Efron and R. Tibshirani, “An Introduction to the Boot strap,” Chapman & Hall, New York, 1993. [6] P. J. Bickel and D. A. Freedman, “Asymptotic Normality and the Bootstrap in Stratified Sampling,” The Annals of Statistics, Vol. 12, No. 2, 1984, pp. 470-482. doi:10.1214/aos/1176346500 [7] J. G. Booth, R. W. Butler and P. Hall, “Bootstrap Methods for Finite Populations,” Journal of the American Statistical Association, Vol. 89, No. 248, 1994, pp. 1282-1289. doi:10.1080/01621459.1994.10476868