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Efficient balanced sampling: The cube method
Abstract
A balanced sampling design is defined by the property that the Horvitz–Thompson estimators of the population totals of a set of auxiliary variables equal the known totals of these variables. Therefore the variances of estimators of totals of all the variables of interest are reduced, depending on the correlations of these variables with the controlled variables. In this paper, we develop a general method, called the cube method, for selecting approximately balanced samples with equal or unequal inclusion probabilities and any number of auxiliary variables.
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Cites
Model Assisted Survey Sampling
Särndal, C.-E., Swensson, B., & Wretman, J. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4378-6 · Cited by 3,386
Introduction to linear and nonlinear programming
Polak, E. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100535 · Cited by 2,100
Neyman, J. (1934) · Journal of the Royal Statistical Society · doi:10.2307/2342192 · Cited by 1,086
Neyman, J. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_12 · Cited by 932
On the Theory of Sampling from Finite Populations
Hansen, M. H., & Hurwitz, W. N. (1943) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177731356 · Cited by 603
Sampling Methods for Censuses and Surveys.
Deming, W. E., & Yates, F. (1949) · Journal of the American Statistical Association · doi:10.2307/2279916 · Cited by 441
Contribution to the Theory of Sampling Human Populations
Neyman, J. (1938) · Journal of the American Statistical Association · doi:10.1080/01621459.1938.10503378 · Cited by 368
Asymptotic Theory of Rejective Sampling with Varying Probabilities from a Finite Population
Hajek, J. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177700375 · Cited by 332
On the Theory of Systematic Sampling, II
Madow, W. G. (1949) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729988 · Cited by 282
Robust Estimation in Finite Populations I
Royall, R. M., & Herson, J. (1973) · Journal of the American Statistical Association · doi:10.1080/01621459.1973.10481440 · Cited by 243
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Handling class imbalance in customer churn prediction
Burez, J., & Van den Poel, D. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.05.027 · Cited by 549
Amin, A., Anwar, S., Adnan, A., Nawaz, M., Howard, N., Qadir, J., Hawalah, A., & Hussain, A. (2016) · IEEE Access · doi:10.1109/access.2016.2619719 · Cited by 310
Spatial cross-validation is not the right way to evaluate map accuracy
Wadoux, A. M. J.-C., Heuvelink, G. B. M., de Bruin, S., & Brus, D. J. (2021) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109692 · Cited by 313
Metadata
- Authors
- Deville, J.-C.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-12-01
- Volume
- 91
- Issue
- 4
- Pages
- 893-912
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2044561565
- Cited by
- 275
- References
- 12
- FWCI
- 2.30
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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