IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v56y2012i7p2219-2236.html
   My bibliography  Save this article

Case-deletion type diagnostics for calibration estimators in survey sampling

Author

Listed:
  • Barranco-Chamorro, I.
  • Jiménez-Gamero, M.D.
  • Moreno-Rebollo, J.L.
  • Muñoz-Pichardo, J.M.

Abstract

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.

Suggested Citation

  • Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Moreno-Rebollo, J.L. & Muñoz-Pichardo, J.M., 2012. "Case-deletion type diagnostics for calibration estimators in survey sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2219-2236.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:7:p:2219-2236
    DOI: 10.1016/j.csda.2011.12.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947311004555
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2011.12.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wu C. & Sitter R. R, 2001. "A Model-Calibration Approach to Using Complete Auxiliary Information From Survey Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 185-193, March.
    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. Changbao Wu, 2003. "Optimal calibration estimators in survey sampling," Biometrika, Biometrika Trust, vol. 90(4), pages 937-951, December.
    4. Cheng, Tsung-Chi, 2011. "Robust diagnostics for the heteroscedastic regression model," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1845-1866, April.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Zaslavsky A. M. & Schenker N. & Belin T. R., 2001. "Downweighting Influential Clusters in Surveys: Application to the 1990 Post Enumeration Survey," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 858-869, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Mayor-Gallego, J.A. & Moreno-Rebollo, J.L., 2015. "A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 18-33.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Changbao Wu & Shixiao Zhang, 2019. "Comments on: Deville and Särndal’s calibration: revisiting a 25 years old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1082-1086, December.
    2. Zhan Liu & Chaofeng Tu & Yingli Pan, 2022. "Model-assisted calibration with SCAD to estimated control for non-probability samples," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 849-879, October.
    3. Sumanta Adhya & Tathagata Banerjee & Gaurangadeb Chattopadhyay, 2012. "Inference on finite population categorical response: nonparametric regression-based predictive approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 69-98, January.
    4. Carl-Erik Särndal & Imbi Traat & Kaur Lumiste, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 183-200, June.
    5. Domingo Morales & María del Mar Rueda & Dolores Esteban, 2018. "Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 873-900, August.
    6. M. Rueda & I. Sánchez-Borrego & A. Arcos & S. Martínez, 2010. "Model-calibration estimation of the distribution function using nonparametric regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(1), pages 33-44, January.
    7. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2019. "A Generalized Calibration Approach Ensuring Coherent Estimates with Small Area Constraints," Research Papers in Economics 2019-10, University of Trier, Department of Economics.
    8. Stearns, Matthew & Singh, Sarjinder, 2008. "On the estimation of the general parameter," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4253-4271, May.
    9. Aylin Alkaya & H. Öztaş Ayhan & Alptekin Esin, 2017. "Sequential Data Weighting Procedures For Combined Ratio Estimators In Complex Sample Surveys," Statistics in Transition New Series, Polish Statistical Association, vol. 18(2), pages 247-270, June.
    10. Särndal Carl-Erik & Traat Imbi & Lumiste Kaur, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 183-200, June.
    11. Barranco-Chamorro, I. & Jiménez-Gamero, M.D. & Mayor-Gallego, J.A. & Moreno-Rebollo, J.L., 2015. "A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 18-33.
    12. Alkaya Aylin & Ayhan H. Öztaş & Esin Alptekin, 2017. "Sequential Data Weighting Procedures for Combined Ratio Estimators in Complex Sample Surveys," Statistics in Transition New Series, Polish Statistical Association, vol. 18(2), pages 247-270, June.
    13. Luis Castro-Martín & María del Mar Rueda & Ramón Ferri-García & César Hernando-Tamayo, 2021. "On the Use of Gradient Boosting Methods to Improve the Estimation with Data Obtained with Self-Selection Procedures," Mathematics, MDPI, vol. 9(23), pages 1-23, November.
    14. Maria del Mar Rueda, 2019. "Comments on: Deville and Särndal’s calibration: revisiting a 25 years old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1077-1081, December.
    15. Jason P. Estes & Bhramar Mukherjee & Jeremy M. G. Taylor, 2018. "Empirical Bayes Estimation and Prediction Using Summary-Level Information From External Big Data Sources Adjusting for Violations of Transportability," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 568-586, December.
    16. Denis Devaud & Yves Tillé, 2019. "Rejoinder on: Deville and Särndal’s calibration: revisiting a 25-year-old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1087-1091, December.
    17. Changbao Wu & Wilson W. Lu, 2016. "Calibration Weighting Methods for Complex Surveys," International Statistical Review, International Statistical Institute, vol. 84(1), pages 79-98, April.
    18. Singh, Sarjinder & Kim, Jong-Min, 2011. "A pseudo-empirical log-likelihood estimator using scrambled responses," Statistics & Probability Letters, Elsevier, vol. 81(3), pages 345-351, March.
    19. Debashis Ghosh & Michael S. Sabel, 2022. "A Weighted Sample Framework to Incorporate External Calculators for Risk Modeling," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 363-379, December.
    20. A.A.M. Nurunnabi & M. Nasser & A.H.M.R. Imon, 2016. "Identification and classification of multiple outliers, high leverage points and influential observations in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(3), pages 509-525, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:56:y:2012:i:7:p:2219-2236. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.