IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v104y2017i1p207-220..html
   My bibliography  Save this article

Itemwise conditionally independent nonresponse modelling for incomplete multivariate data

Author

Listed:
  • Mauricio Sadinle
  • Jerome P. Reiter

Abstract

SUMMARY We introduce a nonresponse mechanism for multivariate missing data in which each study variable and its nonresponse indicator are conditionally independent given the remaining variables and their nonresponse indicators. This is a nonignorable missingness mechanism, in that nonresponse for any item can depend on values of other items that are themselves missing. We show that under this itemwise conditionally independent nonresponse assumption, one can define and identify nonparametric saturated classes of joint multivariate models for the study variables and their missingness indicators. We also show how to perform sensitivity analysis with respect to violations of the conditional independence assumptions encoded by this missingness mechanism. We illustrate the proposed modelling approach with data analyses.

Suggested Citation

  • Mauricio Sadinle & Jerome P. Reiter, 2017. "Itemwise conditionally independent nonresponse modelling for incomplete multivariate data," Biometrika, Biometrika Trust, vol. 104(1), pages 207-220.
    • Handle: RePEc:oup:biomet:v:104:y:2017:i:1:p:207-220.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asw063
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Li, C. & Sun, M. & Wang, Y. & Luo, L. & Yu, M. & Zhang, Y. & Wang, H. & Shi, P. & Chen, Z. & Wang, J. & Lu, Y. & Li, Q. & Wang, X. & Bi, Z. & Fan, M. & Fu, L. & Yu, J. & Hao, M., 2016. "The centers for disease control and prevention system in China: Trends from 2002-2012," American Journal of Public Health, American Public Health Association, vol. 106(12), pages 2093-2102.
    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.
    3. Stasny, Elizabeth A, 1988. "Modeling Nonignorable Nonresponse in Categorical Panel Data with an Example in Estimating Gross Labor-Force Flows," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 207-219, April.
    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. Heng Chen & Daniel F. Heitjan, 2022. "Analysis of local sensitivity to nonignorability with missing outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(4), pages 1342-1352, December.
    2. Olanrewaju Akande & Gabriel Madson & D. Sunshine Hillygus & Jerome P. Reiter, 2021. "Leveraging auxiliary information on marginal distributions in nonignorable models for item and unit nonresponse," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 643-662, April.
    3. Daniel O. Scharfstein & Jon Steingrimsson & Aidan McDermott & Chenguang Wang & Souvik Ray & Aimee Campbell & Edward Nunes & Abigail Matthews, 2022. "Global sensitivity analysis of randomized trials with nonmonotone missing binary outcomes: Application to studies of substance use disorders," Biometrics, The International Biometric Society, vol. 78(2), pages 649-659, June.
    4. Yilin Li & Wang Miao & Ilya Shpitser & Eric J. Tchetgen Tchetgen, 2023. "A self‐censoring model for multivariate nonignorable nonmonotone missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3203-3214, December.

    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. 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.
    2. 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.
    3. Ollinger, Michael & Wilkus, James & Hrdlicka, Megan & Bovay, John, 2017. "Public Disclosure of Tests for Salmonella: The Effects on Food Safety Performance in Chicken Slaughter Establishments," Economic Research Report 262183, United States Department of Agriculture, Economic Research Service.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Berg, G.J. & Lindeboom, M., 1994. "Attrition in panel data and the estimation of dynamic labor market models," Serie Research Memoranda 0022, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    12. 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.
    13. Emre Ekinci & Insan Tunah & Berk Yavuzoglu, 2017. "Rescaled Additivity Non-Ignorable (RAN) Model of Generalized Attrition," Working Papers 1702, Nazarbayev University, Department of Economics, revised Mar 2017.
    14. Hongying Dai & Michael J. Deem & Jianqiang Hao, 2017. "Geographic variations in electronic cigarette advertisements on Twitter in the United States," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(4), pages 479-487, May.
    15. Griffith, Rachel & O’Connell, Martin & Smith, Kate, 2019. "Tax design in the alcohol market," Journal of Public Economics, Elsevier, vol. 172(C), pages 20-35.
    16. Andrew J. Copas & Vern T. Farewell & Catherine H. Mercer & Guiqing Yao, 2004. "The sensitivity of estimates of the change in population behaviour to realistic changes in bias in repeated surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 579-595, November.
    17. Margarita Moreno-Betancur & Grégoire Rey & Aurélien Latouche, 2015. "Direct likelihood inference and sensitivity analysis for competing risks regression with missing causes of failure," Biometrics, The International Biometric Society, vol. 71(2), pages 498-507, June.
    18. Ivy Jansen & Geert Molenberghs & Marc Aerts & Herbert Thijs & Kristel Van Steen, 2003. "A Local Influence Approach Applied to Binary Data from a Psychiatric Study," Biometrics, The International Biometric Society, vol. 59(2), pages 410-419, June.
    19. Ivy Jansen & Ann Van den Troost & Geert Molenberghs & Ad A. Vermulst & Jan R. M. Gerris, 2006. "Modeling Partially Incomplete Marital Satisfaction Data," Sociological Methods & Research, , vol. 35(1), pages 113-136, August.
    20. Monica N. Wymann & Anne Spaar Zographos & Ekkehardt Altpeter & Virginie Masserey Spicher & Nicola Low & Mirjam Mäusezahl-Feuz, 2018. "Human papillomavirus vaccine uptake in adolescence and adherence to cervical cancer screening in Switzerland: a national cross-sectional survey," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(1), pages 105-114, January.

    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:oup:biomet:v:104:y:2017:i:1:p:207-220.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.