Multipurpose Weighting for Small Area Estimation

Journal of Official Statistics

Volumn 25, Issue 3, 2009, Pages 379-395

  Chandra, Hukum ^a   Chambers, Ray ^b  

^a ICAR INDIAN AGRICULTURAL STATISTICS RESEARCH INSTITUTE   (India)

^b UNIVERSITY OF WOLLONGONG   (Australia)

Author keywords

EBLUP; MBD approach; Mixed Model; Multipurpose sample weights; Multivariate surveys

Indexed keywords

EID: 77950766239     PISSN: 0282423X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. Bates, D.M. and Pinheiro, J.C. (1998). Computational Methods for Multilevel Models. Available from http://franz.stat.wisc.edu/pub/NLME/
2. Chambers, R.L. (1996). Robust Case-weighting for Multipurpose Establishment Surveys. Journal of Official Statistics, 12, 3-32.
3. Chambers, R.L. and Tzavidis, N. (2006). M-quantile Models for Small Area Estimation. Biometrika, 93, 255-268. (Pubitemid 43992189)
4. Chandra, H. and Chambers, R.L. (2005). Comparing EBLUP and C-EBLUP for Small Area Estimation. Statistics in Transition, 7, 637-648.
5. Chandra, H., Salvati, N., and Chambers, R.L. (2007). Small Area Estimation for Spatially Correlated Populations. A Comparison of Direct and Indirect Model-based Methods. Statistics in Transition, 8, 887-906.
6. Deville, J.C. and Särndal, C.-E. (1992). Calibration Estimators in Survey Sampling. Journal of the American Statistical Association, 87, 376-382.
7. Prasad, N.G.N. and Rao, J.N.K. (1990). The Estimation of the Mean Squared Error of Small-Area Estimators. Journal of the American Statistical Association, 85, 163-171.
8. Rao, J.N.K. (2003). Small Area Estimation. New York: Wiley.
9. Royall, R.M. (1976). The Linear Least-squares Prediction Approach to Two-stage Sampling. Journal of the American Statistical Association, 71, 657-664.
10. Royall, R.M. and Cumberland, W.G. (1978). Variance Estimation in Finite Population Sampling. Journal of the American Statistical Association, 73, 351-358.
11. Tzavidis, N., Salvati, N., Pratesi, M., and Chambers, R.L. (2008). M-quantile Models with Application to Small Area Estimation and Poverty Mapping. Statistical Methods and Applications, 17, 393-411.