IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v19y2018i2p183-200n2.html
   My bibliography  Save this article

Interaction Between Data Collection And Estimation Phases In Surveys With Nonresponse

Author

Listed:
  • Särndal Carl-Erik

    (Statistics Sweden. Sweden)

  • Traat Imbi

    (Institute of Mathematics and Statistics, University of Tartu, Estonia)

  • Lumiste Kaur

    (Questro Analytics Ltd., Tartu, Estonia)

Abstract

Inference in surveys with nonresponse has been studied extensively in the literature with a focus on the estimation phase. Propensity weighting and calibrated weighting are among the adjustment methods used to reduce the nonresponse bias. The data collection phase has come into focus more recently; the literature on adaptive survey design emphasizes representativeness and degree of balance as desirable properties of the response obtained from a probability sample. We take an integrated view where data collection and estimation are considered together. For a chosen auxiliary vector, we define the concepts incidence and inverse incidence and show their properties and relationship. As we show, incidences are used in balancing the response in data collection; the inverse incidences are important for weighting adjustment in the estimation.

Suggested Citation

  • 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.
  • Handle: RePEc:vrs:stintr:v:19:y:2018:i:2:p:183-200:n:2
    DOI: 10.21307/stattrans-2018-011
    as

    Download full text from publisher

    File URL: https://doi.org/10.21307/stattrans-2018-011
    Download Restriction: no

    File URL: https://libkey.io/10.21307/stattrans-2018-011?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
    ---><---

    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. 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.
    3. 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.
    4. Schouten, Barry & Shlomo, Natalie & Skinner, Chris J., 2011. "Indicators for monitoring and improving representativeness of response," LSE Research Online Documents on Economics 39121, London School of Economics and Political Science, LSE Library.
    5. Roger Tourangeau & J. Michael Brick & Sharon Lohr & Jane Li, 2017. "Adaptive and responsive survey designs: a review and assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 203-223, January.
    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. Barry Schouten & Fannie Cobben & Peter Lundquist & James Wagner, 2016. "Does more balanced survey response imply less non-response bias?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 727-748, June.
    8. J. Michael Brick & Michael E. Jones, 2008. "Propensity to respond and nonresponse bias," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 51-73.
    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. 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.
    2. Roberts Caroline & Herzing Jessica M.E. & Vandenplas Caroline, 2020. "A Validation of R-Indicators as a Measure of the Risk of Bias using Data from a Nonresponse Follow-Up Survey," Journal of Official Statistics, Sciendo, vol. 36(3), pages 675-701, September.
    3. Särndal Carl-Erik & Lundquist Peter, 2017. "Inconsistent Regression and Nonresponse Bias: Exploring Their Relationship as a Function of Response Imbalance," Journal of Official Statistics, Sciendo, vol. 33(3), pages 709-734, September.
    4. Brick J. Michael, 2013. "Unit Nonresponse and Weighting Adjustments: A Critical Review," Journal of Official Statistics, Sciendo, vol. 29(3), pages 329-353, June.
    5. 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.
    6. Stephanie Coffey, PhD. & Jaya Damineni & John Eltinge, PhD. & Anup Mathur, PhD. & Kayla Varela & Allison Zotti, 2023. "Some Open Questions on Multiple-Source Extensions of Adaptive-Survey Design Concepts and Methods," Working Papers 23-03, Center for Economic Studies, U.S. Census Bureau.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Tobias Gummer & Pablo Christmann & Sascha Verhoeven & Christof Wolf, 2022. "Using a responsive survey design to innovate self‐administered mixed‐mode surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 916-932, July.
    12. Jamie C. Moore & Gabriele B. Durrant & Peter W. F. Smith, 2021. "Do coefficients of variation of response propensities approximate non‐response biases during survey data collection?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 301-323, January.
    13. 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.
    14. Barry Schouten & Fannie Cobben & Peter Lundquist & James Wagner, 2016. "Does more balanced survey response imply less non-response bias?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 727-748, June.
    15. 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.
    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. Laaksonen Seppo & Hämäläinen Auli, 2018. "Joint Response Propensity And Calibration Method," Statistics in Transition New Series, Polish Statistical Association, vol. 19(1), pages 45-60, March.
    19. 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.
    20. Brick J. Michael & Tourangeau Roger, 2017. "Responsive Survey Designs for Reducing Nonresponse Bias," Journal of Official Statistics, Sciendo, vol. 33(3), pages 735-752, September.

    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:vrs:stintr:v:19:y:2018:i:2:p:183-200:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.