Abstract
ABSTRACT
A method which is similar to regression estimation method is the calibration estimator. The calibration estimator uses auxiliary variable(s) information to produce efficient estimates. Calibration requires that we know population totals for one or more auxiliary variable (x variables). The efficiency of the calibration estimator depends on how well the auxiliary variables explain the variability of y, the variable of interest. To improve the quality of estimates in sample surveys some kind of weighting is often carried out. This article reviews the calibration estimator which is one of the weighting method and attempts to show calculation of calibration weights with a hypothetical data.
References
- Devılle, J. C. and Särndal, C. E., “Calibration estimators in survey sampling”, Journal of the American Statistical Association, 87: 376-382 (1992).
- Kott, P. S., “On calibration weighting”, http://www.nass.usda.gov/research/reports/2003-jsm-kott.pdf (01.11.2003).
- Betlehem, J. G. and Keller, W. J., “Linear weighting of the sample survey data”, Journal of Official Statistics, Vol.3, 2: 141-153 (1987).
- Kalton, G. and Flores-Cervantes, I., “Weighting methods”, Journal of the American Statistical Association,Vol.19, 2: 81-97 (2003).
- Wu, C. and Sitter, R.R., “A model-calibration approach to using complete auxiliary information from survey data”, Journal of the American Statistical Association, 96: 5-193, (2001).
- Montanari, G. E. and Ranalli M. G., “On calibration methods for design based finite population inferences”, https://www.isi2003.de/guest/IDbb1c3ff5c110b9/?MIval= AbstractView&ABSID=2460, (1.11.2003).
- Creedy, J., Survey Reweighting for tax microsimulation modelling, New Zealand treasury working paper 03/17, http://www.treasury.govt.nz/workingpapers/2003/twp03-17.pdf (September 2003).
- Estevao, V. M. and Särndal C. S, “A functional form approach to calibration”, Journal Of Official Statistics, Vol.16, No.4, 379-399 (2000).
- Särndal, C.E., Swensson, B., and Wretman, J., “Model assisted survey sampling”, Springer, New York (1992).
- Wu, C., “Optimal calibration estimators in survey sampling”, Biometrika, 90, to appear in the December 2003 issue, http://www.stats.uwaterloo.ca/~cbwu/paper.html, 20.10.2003.
- Skinner, C., “Calibration weighting and non-sampling errors”, http://europa.eu.int/comm/ eurostat/research/index.htm?http://europa.eu.int/en/comm/eurostat/research/conferences/ntts-98/agenda.htm&1, 20.12.2004.
Abstract
Regresyon tahmin yöntemine benzeyen bir diğer tahmin yöntemi de ayarlama tahmin edicisi yöntemidir. Ayarlama tahmin edicisi yardımcı değişken(ler) bilgisini tahminlerin etkinliğini arttırmak için kullanır. Ayarlama tahmin edicisi, bir veya birden çok yardımcı değişken (x değişkenleri) için yığın toplamlarını bilmeyi gerektirir. Bu tahmin edicinin etkinliği yardımcı değişken veya değişkenlerin ilgilenilen değişken y’yi ne kadar iyi açıklayabildiğine bağlıdır. Örnekleme araştırmalarında tahminlerin kalitesini arttırmak için bazı ağırlıklandırmalar sıklıkla kullanılmaktadır. Bu çalışmada ağırlıklandırma yöntemlerinden biri olan ayarlama tahmin edicisi incelenmeye çalışılmış, bir hipotetik veri ile ayarlanmış ağırlıkların nasıl hesaplandığı gösterilmeye çalışılmıştır
References
- Devılle, J. C. and Särndal, C. E., “Calibration estimators in survey sampling”, Journal of the American Statistical Association, 87: 376-382 (1992).
- Kott, P. S., “On calibration weighting”, http://www.nass.usda.gov/research/reports/2003-jsm-kott.pdf (01.11.2003).
- Betlehem, J. G. and Keller, W. J., “Linear weighting of the sample survey data”, Journal of Official Statistics, Vol.3, 2: 141-153 (1987).
- Kalton, G. and Flores-Cervantes, I., “Weighting methods”, Journal of the American Statistical Association,Vol.19, 2: 81-97 (2003).
- Wu, C. and Sitter, R.R., “A model-calibration approach to using complete auxiliary information from survey data”, Journal of the American Statistical Association, 96: 5-193, (2001).
- Montanari, G. E. and Ranalli M. G., “On calibration methods for design based finite population inferences”, https://www.isi2003.de/guest/IDbb1c3ff5c110b9/?MIval= AbstractView&ABSID=2460, (1.11.2003).
- Creedy, J., Survey Reweighting for tax microsimulation modelling, New Zealand treasury working paper 03/17, http://www.treasury.govt.nz/workingpapers/2003/twp03-17.pdf (September 2003).
- Estevao, V. M. and Särndal C. S, “A functional form approach to calibration”, Journal Of Official Statistics, Vol.16, No.4, 379-399 (2000).
- Särndal, C.E., Swensson, B., and Wretman, J., “Model assisted survey sampling”, Springer, New York (1992).
- Wu, C., “Optimal calibration estimators in survey sampling”, Biometrika, 90, to appear in the December 2003 issue, http://www.stats.uwaterloo.ca/~cbwu/paper.html, 20.10.2003.
- Skinner, C., “Calibration weighting and non-sampling errors”, http://europa.eu.int/comm/ eurostat/research/index.htm?http://europa.eu.int/en/comm/eurostat/research/conferences/ntts-98/agenda.htm&1, 20.12.2004.
Details
| Primary Language | English |
|---|---|
| Authors | |
| Publication Date | August 11, 2010 |
| IZ | https://izlik.org/JA44ZS97YH |
| Published in Issue | Year 2005 Volume: 18 Issue: 4 |