The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Small Area Estimation: An Appraisal
Open accessAbstract
Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics from both public and private sectors. It is now widely recognized that direct survey estimates for small areas are likely to yield unacceptably large standard errors due to the smallness of sample sizes in the areas. This makes it necessary to "borrow strength" from related areas to find more accurate estimates for a given area or, simultaneously, for several areas. This has led to the development of alternative methods such as synthetic, sample size dependent, empirical best linear unbiased prediction, empirical Bayes and hierarchical Bayes estimation. The present article is largely an appraisal of some of these methods. The performance of these methods is also evaluated using some synthetic data resembling a business population. Empirical best linear unbiased prediction as well as empirical and hierarchical Bayes, for most purposes, seem to have a distinct advantage over other methods.
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Cites
Formulation and estimation of dynamic models using panel data
Anderson, T. W., & Hsiao, C. (1982) · Journal of Econometrics · doi:10.1016/0304-4076(82)90095-1 · Cited by 2,849
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
Kass, R. E., & Steffey, D. (1989) · Journal of the American Statistical Association · doi:10.1080/01621459.1989.10478825 · Cited by 474
Small‐area estimation by combining time‐series and cross‐sectional data
Rao, J. N. K., & Yu, M. (1994) · Canadian Journal of Statistics · doi:10.2307/3315407 · Cited by 195
Self-citationPostcensal Estimates for Local Areas (Or Domains)
Purcell, N. J., & Kish, L. (1980) · International Statistical Review · doi:10.2307/1402400 · Cited by 127
Constrained Bayes Estimation With Applications
Ghosh, M. (1992) · Journal of the American Statistical Association · doi:10.1080/01621459.1992.10475236 · Cited by 118
Self-citationRobust Empirical Bayes Estimation of Means From Stratified Samples
Ghosh, M., & Lahiri, P. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478553 · Cited by 99
Self-citationSome New Estimators for Small-Area Means With Application to the Assessment of Farmland Values
Pfeffermann, D., & Barnard, C. H. (1991) · Journal of Business and Economic Statistics · doi:10.1080/07350015.1991.10509828 · Cited by 60
RYAN, L. M. (2005) · Wiley eBooks · doi:10.1002/0471667196.ess2911.pub2 · Cited by 44
Cited by
Spatial data analysis: theory and practice
(2004) · Choice Reviews Online · doi:10.5860/choice.41-3486 · Cited by 965
Predicting poverty and wealth from mobile phone metadata
Blumenstock, J., Cadamuro, G., & On, R. (2015) · Science · doi:10.1126/science.aac4420 · Cited by 698
The Effect of Improper Priors on Gibbs Sampling in Hierarchical Linear Mixed Models
Hobert, J. P., & Casella, G. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476714 · Cited by 435
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
Standard Errors of Prediction in Generalized Linear Mixed Models
Booth, J. G., & Hobert, J. P. (1998) · Journal of the American Statistical Association · doi:10.1080/01621459.1998.10474107 · Cited by 133
Metadata
- Authors
- Ghosh, M., & Rao, J. N. K.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 1994-02-01
- Volume
- 9
- Issue
- 1
- ISSN
- 0883-4237 (ISSN-L)
- OpenAlex
- W1996995433
- Cited by
- 733
- References
- 9
- FWCI
- 9.55
- Type
- journal article
- Language
- en
- Open access
- bronze
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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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