Abstract
Resampling and replication methods are computer intensive techniques for mitigating the analytic burden of data users through structured and often Monte Carlo simulation-based procedures.
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References
Bickel, P. J., & Freedman, D. A. (1984). Asymptotic normality and the bootstrap in stratified sampling. Annals of Statistics, 12, 470–482.
Booth, J. G., Butler, R. W., & Hall, P. (1994). Bootstrap methods for finite populations. Journal of the American Statistical Association, 89, 1282–1289.
Chauvet, G. (2007). Méthodes de bootstrap en population finie. Ph.D. thesis, Université de Rennes 2.
Chen, S., Haziza, D., Léger, C., & Mashreghi, Z. (2019). Pseudo-population bootstrap methods for imputed survey data. Biometrika, 106, 369–384.
David, H. A. (1968). Gini’s mean difference rediscovered. Biometrika, 55, 573–575.
Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7, 1–26.
Efron, B. (1982). The jackknife, the bootstrap and other resampling plans. Philadelphia: Society for Industrial and Applied Mathematics.
Efron, B. (1994). Missing data, imputation, and the bootstrap. Journal of the American Statistical Association, 89, 463–479.
Fay, R. E. (1984). Some properties of estimators of variance based on replication methods. Proceedings of the Survey Research Methods Section (pp. 495–500). Alexandria, VA: American Statistical Association.
Fay, R. E., & Dippo, C. S. (1989). Theory and application of replicate weighting for variance calculations. Proceedings of the Survey Research Methods Section (pp. 212–217). Alexandria, VA: American Statistical Association.
Gastwirth, J. L. (1971). A general definition of Lorenz curve. Econometrica, 39, 1037–1039.
Gross, S. (1980). Median estimation in sample surveys. Proceedings of the Survey Research Methods Section (pp. 181–184). Alexandria, VA: American Statistical Association.
Holmberg, A. (1998). A bootstrap approach to probability proportional to size sampling. Proceedings of the Survey Research Methods Section (pp. 378–383). Alexandria, VA: American Statistical Association.
Hu, F., & Kalbfleisch, J. D. (2000). The estimating function bootstrap. The Canadian Journal of Statistics, 28, 449–499.
Kim, J. K., & Wu, C. (2013). Sparse and efficient replication variance estimation for complex surveys. Survey Methodology39, 91–120.
Krewski, D., & Rao, J. N. K. (1981). Inference from stratified samples: Properties of linearization, jackknife and balanced repeated replication methods. Annals of Statistics, 9, 1010–1019.
Lorenz, M. O. (1905). Methods of measuring concentration of wealth. Journal of the American Statistical Association, 9, 209–219.
Lu, W. W., & Sitter, R. R. (2008). Disclosure risk and replication-based variance estimation. Statistica Sinica, 18, 1669–1687.
Mashreghi, Z., Haziza, D., & Léger, C. (2016). A survey of bootstrap methods in finite population sampling. Statistics Surveys, 10, 1–52.
McCarthy, P. J. (1966). Replication: An approach to the analysis of data from complex surveys. In Vital and health statistics (Ser. 2, No. 14). Washington, DC: U.S. Government Printing Office.
McCarthy, P. J. (1969). Pseudo-replication: Half samples. Review of the International Statistical Institute, 37, 239–264.
McCarthy, P. J., & Snowden, C. B. (1985). The bootstrap and finite population sampling. In Vital and health statistics (Ser. 2, No. 95). Public health service publication (pp. 85–1369). Washington, DC: U.S. Government Printing Office.
Quenouille, M. (1956). Notes on bias in estimation. Biometrika, 43, 353–360.
Rao, J. N. K., & Shao, J. (1992). Jackknife variance estimation with survey data under hot deck imputation. Biometrika, 79, 811–822.
Rao, J. N. K., & Shao, J. (1996). On balanced half-sample variance estimation in stratified random sampling. Journal of the American Statistical Association, 91, 343–348.
Rao, J. N. K., & Shao, J. (1999). Modified balanced repeated replication for complex survey data. Biometrika, 86, 403–415.
Rao, J. N. K., & Wu, C. F. J. (1985). Inference from stratified samples: second-order analysis of three methods for nonlinear statistics. Journal of the American Statistical Association, 80, 620–630.
Rao, J. N. K., & Wu, C. F. J. (1988). Resampling inference with complex survey data. Journal of the American Statistical Association, 83, 231–241.
Rao, J. N. K., Wu, C. F. J., & Yue, K. (1992). Some recent work on resampling methods for complex surveys. Survey Methodology, 18, 209–217.
Saigo, H. (2010). Comparing four bootstrap methods for stratified three-stage sampling. Journal of Official Statistics, 26, 193–207.
Saigo, H., Shao, J., & Sitter, R. R. (2001). A repeated half-sample bootstrap and balanced repeated replications for randomly imputed data. Survey Methodology, 27, 189–196.
Shao, J., & Sitter, R. R. (1996). Bootstrap for imputed survey data. Journal of the American Statistical Association, 91, 1278–1288.
Shao, J., & Tu, D. (1995). The jackknife and bootstrap. Springer series in statistics. New York: Springer.
Sitter, R. R. (1992a). A resampling procedure for complex survey data. Journal of the American Statistical Association, 87, 755–765.
Sitter, R. R. (1992b). Comparing three bootstrap methods for survey data. The Canadian Journal of Statistics, 20, 135–154.
Tan, Z., & Wu, C. (2015). Generalized pseudo empirical likelihood inferences for complex surveys. The Canadian Journal of Statistics, 43, 1–17.
Wang, Z., & Thompson, M. E. (2012). A resampling approach to estimate variance components of multilevel models. The Canadian Journal of Statistics, 40, 150–171.
Wu, C., & Rao, J. N. K. (2010). Bootstrap procedures for the pseudo empirical likelihood method in sample surveys. Statistics and Probability Letters, 80, 1472–1478.
Wu, C., & Sitter, R. R. (2001b). Variance estimation for the finite population distribution function with complete auxiliary information. The Canadian Journal of Statistics, 29, 289–307.
Zhao, P., Haziza, D., & Wu, C. (2020b). Survey weighted estimating equation inference with nuisance functionals. Journal of Econometrics, 216, 516–536.
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Wu, C., Thompson, M.E. (2020). Resampling and Replication Methods. In: Sampling Theory and Practice. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-44246-0_10
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