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Adaptive cluster sampling with networks selected without replacement
- Source :
- Biometrika. 84:209-219
- Publication Year :
- 1997
- Publisher :
- Oxford University Press (OUP), 1997.
-
Abstract
- SUMMARY In the adaptive cluster design introduced by Thompson (1990), a finite population of units under investigation is partitioned into networks on the basis of a specified condition for adding neighbourhoods to a sampled unit. An initial sample of units is taken and a network may be sampled more than once. In this paper, we introduce a modification of the design in which networks are sampled only once. Two unbiased estimators are considered and the Rao-Blackwell theorem is used to improve them in terms of efficiency. The various estimators are compared using two examples.
- Subjects :
- Statistics and Probability
education.field_of_study
Basis (linear algebra)
Applied Mathematics
General Mathematics
Population
Initial sample
Estimator
Agricultural and Biological Sciences (miscellaneous)
Cluster design
Statistics
Cluster sampling
Statistics, Probability and Uncertainty
General Agricultural and Biological Sciences
education
Unit (ring theory)
Mathematics
Subjects
Details
- ISSN :
- 14643510 and 00063444
- Volume :
- 84
- Database :
- OpenAIRE
- Journal :
- Biometrika
- Accession number :
- edsair.doi...........d1e5b3b94a6830ec96679ffdfe3e9e44