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Case-deletion type diagnostics for calibration estimators in survey sampling

Listed author(s):
  • Barranco-Chamorro, I.
  • Jiménez-Gamero, M.D.
  • Moreno-Rebollo, J.L.
  • Muñoz-Pichardo, J.M.
Registered author(s):

    Based on the use of calibration techniques as a way of handling nonresponse, case-deletion diagnostics for calibration estimators are proposed. A deleted case is dealt with as it were a nonresponse case. Two types of diagnostics are proposed: one compares the calibration weights and the other compares the estimates. These diagnostics are studied in depth for the general regression estimator, and can be calculated from quantities related to the full data set. They are related to the Cook distance and their similarities and differences are highlighted. Both an artificial and a real example are included as illustrations of the diagnostics proposed.

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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 56 (2012)
    Issue (Month): 7 ()
    Pages: 2219-2236

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    Handle: RePEc:eee:csdana:v:56:y:2012:i:7:p:2219-2236
    DOI: 10.1016/j.csda.2011.12.020
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    1. Rondon, Luz Marina & Vanegas, Luis Hernando & Ferraz, Cristiano, 2012. "Finite population estimation under generalized linear model assistance," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 680-697.
    2. Montanari, Giorgio E. & Ranalli, M. Giovanna, 2005. "Nonparametric Model Calibration Estimation in Survey Sampling," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1429-1442, December.
    3. M. Jiménez-Gamero & Juan Moreno-Rebollo & Juan Muñoz-Pichardo & Ana Muñoz-Reyes, 2005. "Influence diagnostics in regression with complex designs through conditional bias," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(2), pages 515-542, December.
    4. Hadi, Ali S., 1992. "A new measure of overall potential influence in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 14(1), pages 1-27, June.
    5. Changbao Wu, 2003. "Optimal calibration estimators in survey sampling," Biometrika, Biometrika Trust, vol. 90(4), pages 937-951, December.
    6. F. J. Breidt & G. Claeskens & J. D. Opsomer, 2005. "Model-assisted estimation for complex surveys using penalised splines," Biometrika, Biometrika Trust, vol. 92(4), pages 831-846, December.
    7. Cheng, Tsung-Chi, 2011. "Robust diagnostics for the heteroscedastic regression model," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1845-1866, April.
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