On the Impact of Bootstrap in Survey Sampling and Small-Area Estimation

Statistical Science

Volumn 18, Issue 2, 2003, Pages 199-210

  Lahiri, P ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

Imputation; Resampling; Small area estimation; Survey weights

Indexed keywords

EID: 0347586775     PISSN: 08834237     EISSN: None     Source Type: Journal    
DOI: 10.1214/ss/1063994975     Document Type: Review

References (57)

1. ARORA, V., LAHIRI, P. and MUKHERJEE, K. (1997). Empirical Bayes estimation of finite population means from complex surveys. J. Amer. Statist. Assoc. 92 1555-1562.
2. BATTESE, G. E., HARTER, R. M. and FULLER, W. A. (1988). An error-components model for prediction of county crop areas using survey and satellite data. J. Amer. Statist. Assoc. 83 28-36.
3. BICKEL, P. J. and FREEDMAN, D. A. (1984). Asymptotic normality and the bootstrap in stratified sampling. Ann. Statist. 12 470-482.
4. BOOTH, J. G. and HOBERT, J. P. (1998). Standard errors of prediction in generalized linear mixed models. J. Amer. Statist. Assoc. 93 262-272.
5. BUTAR, F. B. (1997). Empirical Bayes methods in survey sampling. Ph.D. dissertation, Univ. Nebraska, Lincoln.
6. BUTAR, F. B. and LAHIRI, P. (2003). On measures of uncertainty of empirical Bayes small area estimators. J. Statist. Plann. Inference 112 63-76.
7. CARLIN, B. and GELFAND, A. (1991). A sample reuse method for accurate parametric empirical Bayes confidence intervals. J. Roy. Statist. Soc. Ser B 53 189-200.
8. CHATTERJEE, S. and LAHIRI, P. (2002). Parametric bootstrap confidence interval in small area estimation problems. Unpublished manuscript.
9. CHEN, S. and LAHIRI, P. (2002). A weighted jackknife method in small-area estimation. In ASA Proc. Joint Statistical Meetings 473-477. Amer. Statist. Assoc. Alexandria, VA.
10. COCHRAN, W. G. (1977). Sampling Techniques, 3rd ed. Wiley, New York.
11. DATTA, G. S. and LAHIRI, P. (2000). A unified measure of uncertainty of estimated best linear unbiased predictors in small area estimation problems. Statist. Sinica 10 613-627.
12. EFRON, B. (1979). Bootstrap methods: Another look at the jackknife. Ann. Statist. 7 1-26.
13. EFRON, B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans. SIAM. Philadelphia.
14. EFRON, B. (1987). Better bootstrap confidence intervals (with discussion). J. Amer. Statist. Assoc. 82 171-200.
15. EFRON, B. (1994). Missing data, imputation, and the bootstrap. J. Amer. Statist. Assoc. 89 463-479.
16. FAY, R. E. (1993). Valid inferences from imputed survey data. In Proc. Section on Survey Research Methods 41-48. Amer. Statist. Assoc., Alexandria, VA.
17. FAY, R. E. and HERRIOT, R. A. (1979). Estimates of income for small places: An application of James-Stein procedures to census data. J. Amer. Statist. Assoc. 74 269-277.
18. GAIL, M. H., PFEIFFER, R., VAN HOUWELINGEN, H. C. and CARROLL, R. J. (2000). On meta-analytic assessment of surrogate outcomes. Biostatistics 1 231-246.
19. GHOSH, M. and RAO, J. N. K. (1994). Small area estimation: An appraisal (with discussion). Statist. Sci. 9 55-93.
20. GROSS, S. (1980). Median estimation in sample surveys. In Proc. Section on Survey Research Methods 181-184. Amer. Statist. Assoc., Alexandria, VA.
21. HANSEN, M., HURWITZ, W. and MADOW, W. (1953). Sample Survey Methods and Theory 2. Wiley, New York.
22. JIANG, J., LAHIRI, P. and WAN, S.-M. (2002). A unified jackknife theory for empirical best prediction with M-estimation. Ann. Statist. 30 1782-1810.
23. KACKAR, R. N. and HARVILLE, D. A. (1984). Approximations for standard errors of estimators of fixed and random effects in mixed linear models. J. Amer. Statist. Assoc. 79 853-862.
24. KALTON, G. and KASPRZYK, D. (1986). The treatment of missing survey data. Survey Methodology 12 1-16.
25. KAUFMAN, S. (1996). Estimating the variance in the presence of imputation using a residual. In Proc. Section on Survey Research Methods 423-428. Amer. Statist. Assoc., Alexandria, VA.
26. KOVAR, J. G., RAO, J. N. K. and WU, C.-F. J. (1988). Bootstrap and other methods to measure errors in survey estimates. Canad. J. Statist. 16 25-45.
27. LAHIRI, P. (1995). A jackknife measure of uncertainty of linear empirical Bayes estimators. Unpublished manuscript.
28. LAHIRI, P. and MAITI, T. (2002). Empirical Bayes estimation of relative risks in disease mapping. Calcutta Statist. Assoc. Bull. 53 213-223.
29. LAHIRI, P. and MEZA, J. (2002). Small-area estimation. In Encyclopedia of Environmetrics (A. H. El-Shaarawi and W. W. Piegorsch, eds.) 4 2010-2014. Wiley, New York.
30. LAIRD, N. M. and LOUIS, T. A. (1987). Empirical Bayes confidence intervals based on bootstrap samples (with discussion). J. Amer. Statist. Assoc. 82 739-757.
31. LITTLE, R. J. A. (1986). Survey nonresponse adjustments for estimates of means. Internat. Statist. Rev. 54 139-157.
32. LITTLE, R. J. A. (1993). Pattern-mixture models for multivariate incomplete data. J. Amer. Statist. Assoc. 88 125-134.
33. LITTLE, R. J. A. and RUBIN, D. B. (1987). Statistical Analysis with Missing Data. Wiley, New York.
34. McCARTHY, P. J. and SNOWDEN, C.B. (1985). The bootstrap and finite population sampling. In Vital and Health Statistics 2-95. Public Health Service Publication 85-1369, U. S. Government Printing Office, Washington.
35. MORRIS, C. N. (1983). Parametric empirical Bayes inference: theory and applications (with discussion). J. Amer. Statist. Assoc. 78 47-65.
36. NIGAM, A. K. and RAO, J. N. K. (1996). On balanced bootstrap for stratified multistage samples. Statist. Sinica 6 199-214.
37. PFEFFERMANN, D. (2002). Small area estimation-new developments and directions. Internat. Statist. Rev. 70 125-143.
38. PFEFFERMANN, D. and TILLER, R. (2002). Bootstrap approximation to prediction MSE for state-space models with estimated parameters. Technical report, U.S. Bureau of Labor Statistics.
39. PRASAD, N. G. N. and RAO, J. N. K. (1990). The estimation of the mean squared error of small-area estimators. J. Amer. Statist. Assoc. 85 163-171.
40. RAO, J. N. K. (1996). On variance estimation with imputed survey data. J. Amer. Statist. Assoc. 91 499-506.
41. RAO, J. N. K. (1999). Some recent advances in model-based small area estimation. Survey Methodology 25 175-186.
42. RAO, J. N. K. (2000). Variance estimation in the presence of imputation for missing data. In Proc. Second International Conference on Establishment Surveys. Amer. Statist. Assoc., Alexandria, VA.
43. RAO, J. N. K. and WU, C.-F. J. (1988). Resampling inference with complex survey data. J. Amer. Statist. Assoc. 83 231-241.
44. 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.
45. ROBERTS, G., KOVACEVIC, M., MANTEL, H. and PHILLIPS, O. (2001). Cross-sectional inference based on longitudinal surveys: Some experiences with Statistics Canada surveys. Available at http://www.fcsm.gov/01papers/Mantel.pdf.
46. RUBIN, D. B. (1976). Inference and missing data (with discussion). Biometrika 63 531-592.
47. RUBIN, D. B. (1977). Formalizing subjective notions about the effect of nonrespondents in sample surveys. J. Amer. Statist. Assoc. 72 538-543.
48. RUBIN, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley, New York.
49. RUBIN, D. B. (1994). Discussion of "Missing data, imputation, and the bootstrap," by B. Efron. J. Amer. Statist. Assoc. 89 475-478.
50. 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.
51. RUST, K. F. and RAO, J. N. K. (1996). Variance estimation for complex surveys using replication techniques. Statistical Methods in Medical Research 5 283-310.
52. SAIGO, H., SHAO, J. and SITTER, R. R. (2001). A repeated half-sample bootstrap and balanced repeated replications for randomly imputed data. Survey Methodology 27 189-196.
53. SHAO, J. and SITTER, R. R. (1996). Bootstrap for imputed survey data. J. Amer. Statist. Assoc. 91 1278-1288.
54. SHAO, J. and TU, D. (1995). The Jackknife and Bootstrap. Springer, New York.
55. SITTER, R. R. (1992a). A resampling procedure for complex survey data. J. Amer. Statist. Assoc. 87 755-765.
56. SITTER, R. R. (1992b). Comparing three bootstrap methods for survey data. Canad. J. Statist. 20 135-154.
57. ZHANG, F., BRICK, M., KAUFMAN, S. and WALTER, E. (1998). Variance estimation of imputed survey data. Working Paper 98-14, U.S. Department of Education.