IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v32y2023i1d10.1007_s10260-022-00646-1.html
   My bibliography  Save this article

Generalised calibration with latent variables for the treatment of unit nonresponse in sample surveys

Author

Listed:
  • M. Giovanna Ranalli

    (University of Perugia)

  • Alina Matei

    (University of Neuchâtel)

  • Andrea Neri

    (Banca d’Italia, DG Economics, Statistics and Research)

Abstract

Sample surveys may suffer from nonignorable unit nonresponse. This happens when the decision of whether or not to participate in the survey is correlated with variables of interest; in such a case, nonresponse produces biased estimates for parameters related to those variables, even after adjustments that account for auxiliary information. This paper presents a method to deal with nonignorable unit nonresponse that uses generalised calibration and latent variable modelling. Generalised calibration enables to model unit nonresponse using a set of auxiliary variables (instrumental or model variables), that can be different from those used in the calibration constraints (calibration variables). We propose to use latent variables to estimate the probability to participate in the survey and to construct a reweighting system incorporating such latent variables. The proposed methodology is illustrated, its properties discussed and tested on two simulation studies. Finally, it is applied to adjust estimates of the finite population mean wealth from the Italian Survey of Household Income and Wealth.

Suggested Citation

  • M. Giovanna Ranalli & Alina Matei & Andrea Neri, 2023. "Generalised calibration with latent variables for the treatment of unit nonresponse in sample surveys," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(1), pages 169-195, March.
    • Handle: RePEc:spr:stmapp:v:32:y:2023:i:1:d:10.1007_s10260-022-00646-1
    DOI: 10.1007/s10260-022-00646-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10260-022-00646-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10260-022-00646-1?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. Kott, Phillip S. & Chang, Ted, 2010. "Using Calibration Weighting to Adjust for Nonignorable Unit Nonresponse," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1265-1275.
    2. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    3. Éric Lesage & David Haziza & Xavier D’Haultfœuille, 2019. "A Cautionary Tale on Instrumental Calibration for the Treatment of Nonignorable Unit Nonresponse in Surveys," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 906-915, April.
    4. Andrea Neri & Roberta Zizza, 2010. "Income reporting behaviour in sample surveys," Temi di discussione (Economic working papers) 777, Bank of Italy, Economic Research and International Relations Area.
    5. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.
    6. Ted Chang & Phillip S. Kott, 2008. "Using calibration weighting to adjust for nonresponse under a plausible model," Biometrika, Biometrika Trust, vol. 95(3), pages 555-571.
    Full references (including those not matched with items on IDEAS)

    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. Denis Devaud & Yves Tillé, 2019. "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 1033-1065, December.
    2. Carter, Virginia & Derudder, Ben & Henríquez, Cristián, 2021. "Assessing local governments’ perception of the potential implementation of biophilic urbanism in Chile: A latent class approach," Land Use Policy, Elsevier, vol. 101(C).
    3. Kott Phillip S. & Liao Dan, 2018. "Calibration Weighting for Nonresponse with Proxy Frame Variables (So that Unit Nonresponse Can Be Not Missing at Random)," Journal of Official Statistics, Sciendo, vol. 34(1), pages 107-120, March.
    4. Giovanni D'Alessio & Andrea Neri, 2015. "Income and wealth sample estimates consistent with macro aggregates: some experiments," Questioni di Economia e Finanza (Occasional Papers) 272, Bank of Italy, Economic Research and International Relations Area.
    5. Särndal Carl-Erik & Traat Imbi & Lumiste Kaur, 2018. "Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse," Statistics in Transition New Series, Statistics Poland, vol. 19(2), pages 183-200, June.
    6. Hamori, Shigeyuki & Motegi, Kaiji & Zhang, Zheng, 2019. "Calibration estimation of semiparametric copula models with data missing at random," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 85-109.
    7. Pengfei Li & Jing Qin & Yukun Liu, 2023. "Instability of inverse probability weighting methods and a remedy for nonignorable missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3215-3226, December.
    8. 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.
    9. Kajal Dihidar, 2014. "Estimating population mean with missing data in unequal probability sampling," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(3), pages 369-388, June.
    10. Jordán, Cristian & Speelman, Stijn, 2020. "On-farm adoption of irrigation technologies in two irrigated valleys in Central Chile: The effect of relative abundance of water resources," Agricultural Water Management, Elsevier, vol. 236(C).
    11. 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.
    12. Rueda, M. & Martínez, S. & Illescas, M., 2021. "Treating nonresponse in the estimation of the distribution function," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 186(C), pages 136-144.
    13. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
    14. Shelley H. Liu & Yitong Chen & Jordan R. Kuiper & Emily Ho & Jessie P. Buckley & Leah Feuerstahler, 2024. "Applying Latent Variable Models to Estimate Cumulative Exposure Burden to Chemical Mixtures and Identify Latent Exposure Subgroups: A Critical Review and Future Directions," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 482-502, July.
    15. Lisa Blaydes, 2023. "Assessing the Labor Conditions of Migrant Domestic Workers in the Arab Gulf States," ILR Review, Cornell University, ILR School, vol. 76(4), pages 724-747, August.
    16. Torregrosa-Hetland, Sara, 2016. "Sticky Income Inequality In The Spanish Transition (1973-1990)," Revista de Historia Económica / Journal of Iberian and Latin American Economic History, Cambridge University Press, vol. 34(1), pages 39-80, March.
    17. Arpino, Bruno & Varriale, Roberta, 2009. "Assessing the quality of institutions’ rankings obtained through multilevel linear regression models," MPRA Paper 19873, University Library of Munich, Germany.
    18. Jindřich Špička & Zdeňka Náglová, 2022. "Consumer segmentation in the meat market - The case study of Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(2), pages 68-77.
    19. Nicholas T. Davis & Kirby Goidel & Yikai Zhao, 2021. "The Meanings of Democracy among Mass Publics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 849-921, February.
    20. Byzalov, Dmitri & Basu, Sudipta, 2024. "The misuse of regression-based x-Scores as dependent variables," Journal of Accounting and Economics, Elsevier, vol. 77(2).

    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:spr:stmapp:v:32:y:2023:i:1:d:10.1007_s10260-022-00646-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.