Resampling methods in sample surveys

Statistics

Volumn 27, Issue 3-4, 1996, Pages 203-254

  Shao, Jun ^a,b  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b University of Wisconsin Madison   (United States)

Author keywords

Balanced repeated replication; Bootstrap; Distribution estimation; Functions of weighted averages; Imputation; Jackknife; Sample quantiles; Stratified multistage sampling; Variance estimation

Indexed keywords

EID: 3342921985     PISSN: 02331888     EISSN: None     Source Type: Journal    
DOI: 10.1080/02331889708802523     Document Type: Review

References (51)

1. Bickel, P. J. and Freedman, D. A. (1984). Asymptotic normality and the bootstrap in stratified sampling, Ann. Statist., 12, 470-482.
2. Binder, D. A. and Kovacevic, M. S. (1993). Estimating some measures of income inequality from survey data: An application of the estimating equation approach, preprint.
3. Chao, M. T. and Lo, S. H. (1985). A bootstrap method for finite populations, Sankhyā A, 47, 399-405.
4. Chen, J. and Sitter, R. R. (1993). Edgeworth expansions and the bootstrap for stratified sampling without replacement from a finite population, Canadian J. Statist., 21, 347-357.
5. Cochran, W. G. (1977). Sampling Techniques, third edition, Wiley, New York.
6. Efron, B. (1979). Bootstrap methods: Another look at the jackknife, Ann. Statist., 7, 1-26.
7. Efron, B. (1982). The Jackknife, the Bootstrap, and other Resampling Plans, SIAM, Philadelphia.
8. Efron, B. and Tibshirani, R. (1986). Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy, Statist. Science, 1, 54-77.
9. Fay, R. E. (1991). A design-based perspective on missing data variance, Proceedings of the Seventh Annual Research Conference, 429-440, Bureau of the Census, Washington, D. C.
10. Francisco, C. A. and Fuller, W. A. (1991). Quantile estimation with a complex survey design, Ann. Statist., 19, 454-469.
11. Gross, S. (1980). Median estimation in sampling surveys, Proceedings of the Section on Survey Research Methods, 181-184, American Statistical Association.
12. Gupta, V. K. and Nigam, A. K. (1987). Mixed orthogonal arrays for variance estimation with unequal numbers of primary selections per stratum, Biometrika, 74, 735-742.
13. Gurney, M. and Jewett, R. S. (1975). Constructing orthogonal replications for standard errors, J. Amer. Statist. Assoc., 70, 819-821.
14. Hall, P. (1988). Theoretical comparisons of bootstrap confidence intervals (with discussions), Ann. Statist., 16, 927-953.
15. Kalton, G. (1981). Compensating for Missing Data, ISR research report series. Ann Arbor: Survey Research Center, University of Michigan.
16. Kish, L. and Frankel, M. R. (1974). Inference from complex samples(with discussion), J. R. Statist. Soc. B, 36, 1-37.
17. Kovar, J. G., Rao, J. N. K. and Wu, C. F. J. (1988). Bootstrap and other methods to measure errors in survey estimates, Canadian J. Statist., Supplement, 16, 25-45.
18. Krewski, D. (1978). On the stability of some replication variance estimators in the linear case, J. Statist. Plan. Inf., 2, 45-51.
19. Krewski, D. and Rao, J. N. K. (1981). Inference from stratified samples: properties of the linearization, jackknife and balanced repated replication methods, Ann. Statist., 9, 1010-1019.
20. Liu, J. (1992). Inference from Stratified Samples: Application of Edgeworth Expansions, Ph.D. thesis, Carleton University.
21. McCarthy, P. J. (1969). Pseudo-replication: half samples, Rev. Internat. Statist. Inst., 37, 239-264.
22. McCarthy, P. J. and Snowden, C. B. (1985). The bootstrap and finite population sampling, Vital and Health Statistics, 2-95, Public Health Service Publication 85-1369, U.S. Government Printing Office, Washington, DC.
23. Mantel, H. J. and Singh, A. C. (1991). Standard errors of estimates of low income proportions: a proposed methodology, preprint.
24. Quenouille, M. (1949). Approximation tests of correlation in time series, J. R. Statist. Soc. B, 11, 18-84.
25. Rao, J. N. K. (1979). On deriving mean square errors and their nonnegative unbiased estimators in finite population sampling, J. Indian Statist. Assoc., 17, 125-136.
26. Rao, J. N. K. (1988). Variance estimation in sample surveys, Handbook of Statistics, P. K. Krishnaiah and C. R. Rao eds., 6, 427-447.
27. Rao, J. N. K. and Bellhouse, D. R. (1990). History and development of the theoretical foundations of survey based estimation and analysis, Survey Methodology, 16, 3-39.
28. Rao, J. N. K., Hartley, H. O. and Cochran, W. G. (1962). On a simple procedure of unequal probability sampling without replacement, J. R. Statist. Soc. B, 24, 482-491.
29. Rao, J. N. K. and Shao, J. (1992). Jackknife variance estimation with survey data under hot deck imputation, Biometrika, 79, 811-822.
30. Rao, J. N. K. and Shao, J. (1993). On balanced half-sample variance estimation in stratified sampling, preprint.
31. Rao, J. N. K. and Wu, C. F. J. (1985). Inference from stratified samples: Second-order analysis of three methods for nonlinear statistics, J. Amer. Statist. Assoc., 80, 620-630.
32. Rao, J. N. K. and Wu, C. F. J. (1987). Methods for standard errors and confidence intervals from sample survey data: Some recent work, Bull. Internat. Statist. Inst., Proceedings of the 46th session, 3, 5-19.
33. Rao, J. N. K. and Wu, C. F. J. (1988). Resampling inference with complex survey data, J. Amer. Statist. Assoc., 83, 231-241.
34. Rao, J. N. K., Wu, C. F. J. and Yue, K. (1992). Some recent work on resampling methods for complex surveys, Survey Methodology, 18, 209-217.
35. Rubin, D. B. (1978). Multiple imputations in sample surveys-a phenomenological Bayesian approach to nonresponse, Proceedings of the Survey Research Methods Section, 20-34, American Statistical Association.
36. Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys, Wiley, New York.
37. Rubin, D. B. and Schenker, N. (1986). Multiple imputation for interval estimation from simple random samples with ignorable nonresponse, J. Amer. Statist. Assoc., 81, 366-374.
38. Schenker, N. and Welsh, A. H. (1988). Asymptotic results for multiple imputation, Ann. Statist., 16, 1550-1566.
39. Sedransk, J. (1985). The objective and practice of imputation, Proceedings of the First annual Research Conference, 445-452, Bureau of the Census, Washington D.C.
40. Shao, J. (1989). The efficiency and consistency of approximations to the jackknife variance estimators, J. Amer. Statist. Assoc., 84 114-119.
41. Shao, J. (1994). L-statistics in complex surveys, Ann. Statist., 22, 946-967.
42. Shao, J. and Rao, J. N. K. (1994). Standard errors for low income proportions estimated from stratified multistage samples, Sankhyā B, 55, 393-414.
43. Shao, J. and Sitter, R. R. (1993). Bootstrap for imputed survey data, preprint.
44. Shao, J. and Wu, C. F. J. (1989). A general theory for jackknife variance estimation, Ann. Statist., 17, 1176-1197.
45. Shao, J. and Wu, C. F. J. (1992). Asymptotic properties of the balanced repeated replication method for sample quantile, Ann. Statist., 20, 1571-1593.
46. Sitter, R. R. (1992a). A resampling procedure for complex survey data, J. Amer. Statist. Assoc., 87, 755-765.
47. Sitter, R. R. (1992b). Comparing three bootstrap methods for survey data, Canadian J. Statist. 20, 135-154.
48. Sitter, R. R. (1993). Balanced repeated replications based on orthogonal multi-arrays, Biometrika, 80, 211-221.
49. Tukey, J. (1958). Bias and confidence in not quite large samples, Ann. Math. Statist., 29, 614.
50. Woodruff, R. S. (1952). Confidence intervals for medians and other position measures, J. Amer. Statist. Assoc., 47, 635-646.
51. Wu, C. F. J. (1991). Balanced repeated replications based on mixed orthogonal arrays, Biometrika, 78, 181-188.