The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Small Area Estimation
Abstract
Abstract This article provides an overview of methods for estimating small‐area means or totals when the area‐specific sample sizes are small. Methods studied include indirect methods based on implicit models and methods based on explicit models.
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Cites
Parametric empirical Bayes inference: theory and applications
Morris, C. N. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10477920 · Cited by 1,448
Cited by
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Struggles with Survey Weighting and Regression Modeling
Gelman, A. (2007) · Statistical Science · doi:10.1214/088342306000000691 · Cited by 604
The interplay of Bayesian and frequentist analysis
Bayarri, M. J., & Berger, J. O. (2004) · Statistical Science · doi:10.1214/088342304000000116 · Cited by 525
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Patterns and causes of uncertainty in the American Community Survey
Spielman, S. E., Folch, D., & Nagle, N. (2014) · Applied Geography · doi:10.1016/j.apgeog.2013.11.002 · Cited by 278
Metadata
- Authors
- Rao, J. N. K.
- Venue
- Encyclopedia of Statistical Sciences
- Publisher
- Wiley
- Published
- 2004-10-15
- Pages
- 1-139
- OpenAlex
- W1484712862
- Cited by
- 2,049
- References
- 1
- Type
- reference entry
- Language
- en
- Open access
- closed
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- Rao, J. N. K. (2004). Small Area Estimation. Encyclopedia of Statistical Sciences. https://doi.org/10.1002/0471667196.ess0731
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
