IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v66y2017i5p1049-1064.html
   My bibliography  Save this article

Mechanism for missing data incorporated in joint modelling of ordinal responses

Author

Listed:
  • Anna Ivanova
  • Geert Molenberghs
  • Geert Verbeke

Abstract

No abstract is available for this item.

Suggested Citation

  • Anna Ivanova & Geert Molenberghs & Geert Verbeke, 2017. "Mechanism for missing data incorporated in joint modelling of ordinal responses," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 1049-1064, November.
  • Handle: RePEc:bla:jorssc:v:66:y:2017:i:5:p:1049-1064
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssc.12201
    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. Samuel Iddi & Geert Molenberghs, 2012. "A joint marginalized multilevel model for longitudinal outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2413-2430, July.
    2. Steffen Fieuws & Geert Verbeke, 2006. "Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles," Biometrics, The International Biometric Society, vol. 62(2), pages 424-431, June.
    3. Steffen Fieuws & Geert Verbeke & Filip Boen & Christophe Delecluse, 2006. "High dimensional multivariate mixed models for binary questionnaire data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 449-460, August.
    4. Geert Molenberghs & Caroline Beunckens & Cristina Sotto & Michael G. Kenward, 2008. "Every missingness not at random model has a missingness at random counterpart with equal fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 371-388, April.
    5. Joseph L. Schafer, 2003. "Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 19-35, February.
    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. Jeonghye Choi & David R. Bell & Leonard M. Lodish, 2012. "Traditional and IS-Enabled Customer Acquisition on the Internet," Management Science, INFORMS, vol. 58(4), pages 754-769, April.
    2. A.Y. Kombo & H. Mwambi & G. Molenberghs, 2017. "Multiple imputation for ordinal longitudinal data with monotone missing data patterns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 270-287, January.
    3. Alexander Robitzsch, 2024. "A Comparison of Limited Information Estimation Methods for the Two-Parameter Normal-Ogive Model with Locally Dependent Items," Stats, MDPI, vol. 7(3), pages 1-16, June.
    4. Margaux Delporte & Steffen Fieuws & Geert Molenberghs & Geert Verbeke & Simeon Situma Wanyama & Elpis Hatziagorou & Christiane De Boeck, 2022. "A joint normal‐binary (probit) model," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 37-51, December.
    5. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.
    6. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
    7. Molenberghs, Geert & Verbeke, Geert & Iddi, Samuel, 2011. "Pseudo-likelihood methodology for partitioned large and complex samples," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 892-901, July.
    8. Celine Marielle Laffont & Marc Vandemeulebroecke & Didier Concordet, 2014. "Multivariate Analysis of Longitudinal Ordinal Data With Mixed Effects Models, With Application to Clinical Outcomes in Osteoarthritis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 955-966, September.
    9. Yekun Qin & Shanminhui Yin & Fang Liu, 2024. "RETRACTED ARTICLE: Navigating Criminal Responsibility in the Digital Marketplace: Implications of Network-Neutral Help Behavior and Beyond-5G Networks in E-Commerce Transactions," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 10667-10695, September.
    10. Yungtai Lo, 2017. "Joint modeling of bottle use, daily milk intake from bottles, and daily energy intake in toddlers," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2301-2316, October.
    11. Chuan Hong & Yang Ning & Peng Wei & Ying Cao & Yong Chen, 2017. "A semiparametric model for vQTL mapping," Biometrics, The International Biometric Society, vol. 73(2), pages 571-581, June.
    12. Yuriko Takeda & Toshihiro Misumi & Kouji Yamamoto, 2022. "Joint Models for Incomplete Longitudinal Data and Time-to-Event Data," Mathematics, MDPI, vol. 10(19), pages 1-7, October.
    13. Brick J. Michael, 2013. "Unit Nonresponse and Weighting Adjustments: A Critical Review," Journal of Official Statistics, Sciendo, vol. 29(3), pages 329-353, June.
    14. Brenden Bishop & Minjeong Jeon, 2016. "Book Review," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 1164-1167, December.
    15. Jesús Rascón & Wildor Gosgot Angeles & Manuel Oliva-Cruz & Miguel Ángel Barrena Gurbillón, 2022. "Wind Characteristics and Wind Energy Potential in Andean Towns in Northern Peru between 2016 and 2020: A Case Study of the City of Chachapoyas," Sustainability, MDPI, vol. 14(10), pages 1-11, May.
    16. Christopher H. Morrell & Larry J. Brant & Shan Sheng & E. Jeffrey Metter, 2012. "Screening for prostate cancer using multivariate mixed-effects models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1151-1175, November.
    17. Padayachee Trishanta & Khamiakova Tatsiana & Shkedy Ziv & Salo Perttu & Perola Markus & Burzykowski Tomasz, 2019. "A multivariate linear model for investigating the association between gene-module co-expression and a continuous covariate," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(2), pages 1-13, April.
    18. Marco Doretti & Martina Raggi & Elena Stanghellini, 2022. "Exact parametric causal mediation analysis for a binary outcome with a binary mediator," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 87-108, March.
    19. Hillary Koch & Cheryl A. Keller & Guanjue Xiang & Belinda Giardine & Feipeng Zhang & Yicheng Wang & Ross C. Hardison & Qunhua Li, 2022. "CLIMB: High-dimensional association detection in large scale genomic data," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Roula Tsonaka & Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre, 2010. "Nonignorable Models for Intermittently Missing Categorical Longitudinal Responses," Biometrics, The International Biometric Society, vol. 66(3), pages 834-844, September.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssc:v:66:y:2017:i:5:p:1049-1064. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.