MutiplicitySampling&VariantsBiblio.doc
©2010, Timothy G. Gregoire, Yale University
LAST REVISED: NOVEMBER 2010 MUTIPLICITY SAMPLING& VARIANTS BIBLIOGRAPHY
1965-Present
1. Anonymous.U.S. Department of Health, Education and Welfare. 1965. “Design of
Sample Surveys to Estimate the Prevalence of Rare Diseases: Three Unbiased
Estimates”. National Center for Health Statistics, 2(11): 1-8.
2. Sirken, M. G. 1970. “Household Surveys with Multiplicity.”Journal of the American
Statistical Association, 65(329):257-266.
3. Sirken, M. G. 1972. “Stratified Sample Surveys with Multiplicity.” Journal of the
American Statistical Association, 67(337):224-227.
4. Sirken, M. G.1972. “Survey Strategies for Estimating Rare Health Attributes.”
Proceedings,Sixth Berkeley Symposium on Mathematical Statistics and Probability 1972
volume VI.
5. Sirken, M. G. 1972.“Variance Components of Multiplicity Estimators.” Biometrics,
28(3):869-873.
6. Sirken, M. G.1973.“Design of Household Sample Surveys to test Death Registration
Completeness.” Demography, 10 (3):469-478
7. Sirken, M. G. and Levy, P. S. 1974.“Multiplicity Estimation of Proportions Based on
Ratios of Random Variables.” Journal of the American Statistical Association,
69(345):68-73.
8. Sirken, M. G. 1975. “Discussion of Medical Provider Surveys of Neurological
Conditions.” Proceedings of the American Statistical Association, 56-58.
9. Sirken, M. G. 1975.”Network Surveys.” Proceedings of the 40th Section, Bulletin of the
International Statistical Institute, 332-342.
10. Sirken, M. G. and Royston, P. N. 1977. “Counting Rule Bias in Household Surveys of
Deaths.” Proceedings of the American Statistical Association, 347-351.
11. Sirken, M. G., Graubard, B. J. and LaValley, R. W. 1978. “Evaluation of Census
Population Coverage by Network Surveys.” Proceedings of the Section on Survey
Research Methods, 239-244.
12. Sirken, M. G. 1978. “Dual System Estimators Based on Multiplicity Surveys.” The
University of Alberta Press, Karol J. Krotti (ed.), pp.81-91.
MutiplicitySampling&VariantsBiblio.doc
©2010, Timothy G. Gregoire, Yale University
13. Sirken, M. G. 1980. “Effects of Counting Rules and Estimators on the Data Requirements
in a National Hospital Patient Survey.” Proceedings of the American Statistical
Association, 177-179. 14. Sirken, M. G. 1983. “Handling Missing Data by Network Sampling.”Incomplete Data in
Sample Surveys, 2(II):81-90. 15. Kalton, G. and Anderson, D. W. 1986. “Sampling Rare Populations.”The Journal of the
Royal Statistical Society, 149(1):65-82.
16. Czaja, R. F., Snowden, C. B. and Casady, R. J. 1986. “Reporting Bias and Sampling
Errors in a Survey of a Rare Population Using Multiplicity Counting Rules.” Journal of
the American Statistical Association, 81(394):411-419.
17. Sudman,S., Sirken, M. G and Cowan, C. D. 1988. “Sampling Rare and Elusive
Populations.” Science, 240: 991-995Besag, J. and Newell, J. 1991. “The Detection of
Clusters in Rare Diseases.” The Journal of the Royal Statistical Society, 154(1):143-155.
18. Thompson, S. K. 1989. “Adaptive Cluster Sampling.” Institute of Mathematical
Statistics, University of Copenhagen, 5:1-31.
19. Czaja, R. and Blair, J. 1990. “Using Network Sampling in Crime Victimization Surveys.”
Journal of Quantitative Criminology.
20. Thompson, S. K. 1990. “Adaptive Cluster Sampling.” Journal of the American Statistical
Association, 85(412):1050-1059.
21. Besag, J. and Newell, J. 1991. “The Detection of Clusters in Rare Diseases.” The Journal
of the Royal Statistical Society, 154(1):143-155.
22. Thompson, S. K. 1991. “Adaptive Cluster Sampling: Designs with Primary and
Secondary Units.” Biometrics, 47: 1103-1115.
23. Thompson, S. K. 1991. “Stratified Adaptive Cluster Sampling.” Biometrika, 78(2): 389397.
24. Thompson, S. K ., Ramsey, F. L. and Seber, G. A. F. 1992. “An Adaptive Procedure for
Sampling Animal Populations.” Biometrics, 48:1195-1199.
25. Green, R.H and Young, R.C. 1993. “Sampling to Detect Rare Species”. Ecological
Applications, 3(2): 351-356.
26. Roesch Jr., F. A. 1993. “Adaptive Cluster Sampling for Forest Inventories.” Forest
Science, 39(4):655-669.
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MutiplicitySampling&VariantsBiblio.doc
©2010, Timothy G. Gregoire, Yale University
27. Roesch, F.A. 1994. “Incorporating Estimates of Rare Clustered Events into Forest
Inventories.” Journal of Forestry, 92(12): 31-34.
28. Seber, G. A. F. and Thompson, S. K. 1994. “Environmental Adaptive Sampling.”
Handbook of Statistics: Environmental Statistics, 12:201-220.
29. Thompson, S. K. and Seber, G. A. F. 1994. “Detectability in Conventional and Adaptive
Sampling.” Biometrics, 50:712-724.
30. Smith, D. R., Conroy, M. J. and Brakhage, D. H. 1995. “Efficiency of Adaptive Cluster
Sampling for Estimating Density of Wintering Waterfowl.”Biometrics, 51: 777-788.
31. Christman, M.C. 1996. “Comparison of Efficiently of Adaptive Sampling in some
Spatially Clustered Populations.” American Statistical Association. Proceedings of the
Section on Statistics and the Environment, 123-126.
32. Christman, M.C. 1997. “Efficiency of Some Sampling Designs for Spatially Clustered
Populations.” Environmetrics, 8: 145-166.
33. Pontius, J. S. 1997. “Strip Adaptive Cluster Sampling: Probability Proportional to Size
Selection of Primary Units.” Biometrics, 53:1092-1096.
34. Mohammed, S. M., and Seber G. A. F. 1997. “Two-Stage Adaptive Cluster Sampling”.
Biometrics, 53(3): 1-22.
35. Brown, J. A. and Manly, B. J. F. 1998. “Restricted
Sampling.”Environmental and Ecological Statistics, 5: 49-63.
Adaptive
Cluster
36. Salehi, M. M. 1999. “Rao-Blackwell versions of the Horvitz-Thompson and Hansen –
Hurwitz in adaptive cluster sampling.” Environmental and Ecological Statistics,6:183195.
37. Acharya, B., Bhattarai, G., and Stein, A. 2000. “Systematic Adaptive Cluster Sampling
for the Assessment of Rare Tree Species in Nepal.”Forest Ecology and Management,
137: 65 - 73.
38. Chaudhuri, A. 2000. “Network and Adaptive Sampling with Unequal Probabilties.”
Calcutta Statistical Association Bulletin, 50: 199-200.
39. Christman, M.C. 2000. “A Review of Quadrat-Based Sampling of Rare, Geographically
Clustered Populations”. Journal of Agricultural, Biological, and Environmental
Statistics, 5(2): 168-201.
40. Christman, M.C. and Pontius, J.S. 2000. “Bootstrap Confidence Intervals for Adaptive
Cluster Sampling”. Biometrics, 56: 503-510.
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MutiplicitySampling&VariantsBiblio.doc
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41. Thompson, S. K. and Frank, O. 2000.“Model-Based Estimation With Link-Tracing
Sampling Designs.” Survey Methodology,26(1):87-98.
42. Chao, C-T and Thompson, S. K. 2001. “Optimal adaptive selection of sampling sites.”
Environmetrics, 12:517-538.
43. Christman, M. C. and Lan, F. 2001. “Inverse Adaptive Cluster Sampling.” Biometrics,
57: 1096-1105.
44. Salehi, M. M. 2001. Application of Adaptive Sampling in Fishery Part 2: Truncated
Adaptive Cluster Sampling Designs.” Iranian Fisheries Sciences,3(1):77-84.
45. Salehi, M. M.,and Seber, G. A. F. 2002. “Unbiased estimators for restricted adaptive
cluster sampling.” Australian and New Zealand Journal of Statistics, 44:63-74
46. Thompson, S. K. 2002. “Adaptive Sampling.” REVIEWED BY Professor Tim Gregoire
47. Brown, J. A. 2003. “Designing an efficient adaptive cluster sample.” Environmental and
Ecological Statistics, 10: 95-105.
48. Green, R.H. 2003. “Estimating the Characteristics of Dispersed Populations of Sawlogs
Under Adverse Field Conditions-Field Trials of Adaptive Cluster Sampling”. Joint
Conference of Southern Forest Mensurationist Organisation, pp 1-16.
49. Hanselman, D.H., Quinn II, T.J., Lunsford, C., Heifetz, J. and Clausen, D. 2003.
“Applications in Adaptive Cluster Sampling of Gulf of Alaska Rockfish”. Fishery
Bulletin, 101(3):501-513.
50. Smith, D. R. Villella, R. and Lemarié, D. P. 2003. “Application of Adaptive Cluster
Sampling to Low-Density Populations of Freshwater Mussels”. Environmental and
Ecological Statistics, 10(7-15).
51. Chaudhuri, A. , Bose, M. and Ghosh, J. K. 2004. “An application of adaptive sampling to
estimate highly localized population segments.” Journal of Statistical Planning and
Inference, 121: 175-189.
52. Félix-Medina, M. H. and Thompson, S. K. 2004. “Combining Link-Tracing Sampling
and Cluster Sampling to Estimate the Size of Hidden Populations. Journal of Offìcial
Statistics, 20(1): 1-20.
53. Naddeo, S. and Pisani, C. 2004.“A critical look at adaptive sampling.” Proceedings of the
XLII Meeting of The Italian Statistical Society. 54. Smith, D. R., Brown, J. A. and Lo, N. C. H. 2004“Application of Adaptive Sampling to
Biological Populations.”Kenneth P. Burnham (ed.) Island Press, 77-121.
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MutiplicitySampling&VariantsBiblio.doc
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55. Dryver, A. L. and Thompson, S. K. 2005. “Improved unbiased estimators in adaptive
cluster sampling.”Royal Statistical Society, 67(1): 157-166.
56. Magussen, S., Kurz, W., Leckie, D.G. and Paradine, D. 2005. “Adaptive Cluster
Sampling for Estimation of Deforestation Rates.” European Journal of Forest Resources,
124 :207-220.
57. Mohammed, S. M. and Smith, D. R. 2005. “Two- Stage Sequential Sampling: A
Neighbourhood-Free Adaptive Sampling Procedure.” Journal of Agricultural, Biological
and Environmental Statistics, 10(1): 84- 103.
58. Naddeo, S. and Pisani, C. 2005. “Two-Stage Adaptive Cluster Sampling”. 2005.
Statistical Methods & Applications, 14: 3-10.
59. Oja, S. 2005. “Inventory of Sparse Forest Populations Using Adaptive Cluster
Sampling”. Silva Fennica,pp. 1-19.
60. Saheli, M. M. and Smith, D. R. 2005. “Two-stage sequential sampling design: a
neighbourhood-free adaptive sampling procedure.” Journal of Agriculture, Biological
and Environmental Statistics, 10(1):84-103.
61. Turk, P. and Borkowski, J. J. 2005. “Review of Adaptive Cluster Sampling: 1990-2003.”
Environmental and Ecological Statistics, 12: 55-94.
62. Talvite, M., Leino, O. and Thompson, M. 2006. “Inventory of Sparse Forest Populations
Using Adaptive Cluster Sampling.” Silva Fennica, 40(1):101-108.
63. Thompson, S. K. 2006. “Targeted Random Walk Designs”. Survey Methodology,
32(1):11-24.
64. Thompson, S. K. 2006. “Adaptive Web Sampling.” Biometrics, 62:1224-1234.
65. Dryver, A. L. and Chao, C.-T. 2007. “Ratio Estimators in Adaptive Cluster Sampling”.
Environmetrics, 18: 607-620. Environmental and Ecological Statistics, 10: 95-105.
66. Brown, J. A., Salehi, M. M., Gavin, B. and Smith, D. R. 2008. “An adaptive two-stage
sequential deign for sampling and clustered populations.” Population Ecology, 50: 239245.
67. Moradi, M. and Saheli, M. 2010. “An adaptive allocation sampling design for which the
conventional stratified estimator is an appropriate estimator.” Journal of Statistical
Planning and Inference, 140(4):1030-1037.
68. Salehi, M. M. and Brown, J. A. 2010. “Complete allocation sampling: An efficient and
easily implemented adaptive sampling design.” Population Ecology, 52(3):451-456.
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69. Salehi, M. M., Moradi, M., Brown, J. A. and Smith D. R. 2010. “Efficient estimators for
adaptive stratified sequential sampling.” Journal of Statistical Computation and
Simulation, 80(10):1163-1179.
70. Salehi, M. M., Mohammadi, M., Rao, J. N. K., and Berger, Y. G. 2010. “Empirical
Likelihood Confidence Intervals for Adaptive Cluster Sampling.” Environmental and
Ecological Statistics, 17:111-123.
71. Thompson, S. K. 2010. “Adaptive network and spatial sampling.”Survey Methodology (in
press), 41pp.
72. Makarovič, B. ####. “Progressive sampling for digital terrain models.” 397-415.
73. Dutka, S.#####.“Sampling rare populations: an alternative method.”Audits &Surveys,
INC.One Park Avenue, New York, N.Y.,(212):683-3500.
74. Mohammed, S. M.#### “Comparison Between Hansen-Hurwitz and Horvitz-Thompson
Estimators for Adaptive Cluster Sampling.”
75. Thompson, S. K and Collins, L. M. ####“Adaptive Sampling in Research on RiskRelated Behaviors.” 1-45
76. Chow, M. and Thompson, S. K. #####. “Estimation with Link-Tracing Sampling
Designs-A Bayesian Approach.” 1-27
77. Thompson, S. K. ####. “Adaptive Sampling of Animal Populations.” Technical Report
82: 1-20.
78. Félix-Medina, M. H. and Thompson, S. K.#####. “Adaptive Cluster Double
Sampling.”1-26
79. Using Network Sampling in Crime Victimization Surveys.####.”Journal of Quantitative
Criminology, 6(2):185-206.
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