IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v75y2012i5p581-599.html
   My bibliography  Save this article

Fractional imputation for incomplete two-way contingency tables

Author

Listed:
  • Shin-Soo Kang
  • Kenneth Koehler
  • Michael Larsen

Abstract

No abstract is available for this item.

Suggested Citation

  • Shin-Soo Kang & Kenneth Koehler & Michael Larsen, 2012. "Fractional imputation for incomplete two-way contingency tables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 581-599, July.
    • Handle: RePEc:spr:metrik:v:75:y:2012:i:5:p:581-599
    DOI: 10.1007/s00184-011-0343-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00184-011-0343-y
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00184-011-0343-y?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. Jae Kwang Kim, 2004. "Fractional hot deck imputation," Biometrika, Biometrika Trust, vol. 91(3), pages 559-578, September.
    2. Geert Molenberghs & Michael G. Kenward & Els Goetghebeur, 2001. "Sensitivity analysis for incomplete contingency tables: the Slovenian plebiscite case," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(1), pages 15-29.
    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. Chen, Sixia & Haziza, David, 2023. "A unified framework of multiply robust estimation approaches for handling incomplete data," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    2. Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
    3. Frederico Poleto & Geert Molenberghs & Carlos Paulino & Julio Singer, 2011. "Sensitivity analysis for incomplete continuous data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 589-606, November.
    4. Yijie Xue & Nicole Lazar, 2012. "Empirical likelihood-based hot deck imputation methods," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 629-646.
    5. Frederico Z. Poleto & Julio M. Singer & Carlos Daniel Paulino, 2011. "Comparing diagnostic tests with missing data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(6), pages 1207-1222, April.
    6. Gelein, Brigitte & Haziza, David & Causeur, David, 2014. "Preserving relationships between variables with MIVQUE based imputation for missing survey data," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 197-208.
    7. Caroline Beunckens & Cristina Sotto & Geert Molenberghs & Geert Verbeke, 2009. "A multifaceted sensitivity analysis of the Slovenian public opinion survey data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 171-196, May.
    8. Jeongsub Choi & Youngdoo Son & Myong K. Jeong, 2024. "Gaussian kernel with correlated variables for incomplete data," Annals of Operations Research, Springer, vol. 341(1), pages 223-244, October.
    9. Baojiang Chen & Xiao-Hua Zhou, 2011. "Doubly Robust Estimates for Binary Longitudinal Data Analysis with Missing Response and Missing Covariates," Biometrics, The International Biometric Society, vol. 67(3), pages 830-842, September.
    10. Mauricio Sadinle & Jerome P. Reiter, 2017. "Itemwise conditionally independent nonresponse modelling for incomplete multivariate data," Biometrika, Biometrika Trust, vol. 104(1), pages 207-220.
    11. Xiaojun Mao & Zhonglei Wang & Shu Yang, 2023. "Matrix completion under complex survey sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 463-492, June.
    12. Danhyang Lee & Jae Kwang Kim, 2022. "Semiparametric imputation using conditional Gaussian mixture models under item nonresponse," Biometrics, The International Biometric Society, vol. 78(1), pages 227-237, March.
    13. Helene Boistard & Guillaume Chauvet & David Haziza, 2016. "Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 683-699, September.
    14. Ivy Jansen & Geert Molenberghs, 2008. "A flexible marginal modelling strategy for non‐monotone missing data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 347-373, April.
    15. Qin, Yongsong & Rao, J.N.K. & Ren, Qunshu, 2008. "Confidence intervals for marginal parameters under fractional linear regression imputation for missing data," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1232-1259, July.
    16. D. Nitsch & B. L. DeStavola & S. M. B. Morton & D. A. Leon, 2006. "Linkage bias in estimating the association between childhood exposures and propensity to become a mother: an example of simple sensitivity analyses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 493-505, July.
    17. Andrzej S. Kosinski & Huiman X. Barnhart, 2003. "Accounting for Nonignorable Verification Bias in Assessment of Diagnostic Tests," Biometrics, The International Biometric Society, vol. 59(1), pages 163-171, March.
    18. Kim, Seongyong & Park, Yousung & Kim, Daeyoung, 2015. "On missing-at-random mechanism in two-way incomplete contingency tables," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 196-203.
    19. Ton de Waal & Wieger Coutinho, 2017. "Preserving Logical Relations while Estimating Missing Values," Romanian Statistical Review, Romanian Statistical Review, vol. 65(3), pages 47-59, September.
    20. Skinner, Chris J., 2007. "Discussion of J.F.Bjørnstad, ‘Non-Bayesian multiple imputation’," LSE Research Online Documents on Economics 39107, London School of Economics and Political Science, LSE Library.

    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:metrik:v:75:y:2012:i:5:p:581-599. 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.