IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i1p280-289.html
   My bibliography  Save this article

Semiparametric Bayesian Inference for Multilevel Repeated Measurement Data

Author

Listed:
  • Peter Müller
  • Fernando A. Quintana
  • Gary L. Rosner

Abstract

No abstract is available for this item.

Suggested Citation

  • Peter Müller & Fernando A. Quintana & Gary L. Rosner, 2007. "Semiparametric Bayesian Inference for Multilevel Repeated Measurement Data," Biometrics, The International Biometric Society, vol. 63(1), pages 280-289, March.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:1:p:280-289
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00668.x
    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. Browne, William J. & Draper, David & Goldstein, Harvey & Rasbash, Jon, 2002. "Bayesian and likelihood methods for fitting multilevel models with complex level-1 variation," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 203-225, 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. Savitsky, Terrance & Paddock, Susan, 2014. "Bayesian Semi- and Non-Parametric Models for Longitudinal Data with Multiple Membership Effects in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i03).

    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. Abrahantes, Jose Cortinas & Molenberghs, Geert & Burzykowski, Tomasz & Shkedy, Ziv & Abad, Ariel Alonso & Renard, Didier, 2004. "Choice of units of analysis and modeling strategies in multilevel hierarchical models," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 537-563, October.
    2. Brandon LeBeau & Yoon Ah Song & Wei Cheng Liu, 2018. "Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis," SAGE Open, , vol. 8(4), pages 21582440188, December.
    3. William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
    4. V. Simonite & W. J. Browne, 2003. "Estimation of a large cross‐classified multilevel model to study academic achievement in a modular degree course," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 119-133, February.
    5. Daniel McNeish & Denis Dumas & Dario Torre & Neil Rice, 2022. "Modelling time to maximum competency in medical student progress tests," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2007-2034, October.
    6. Alan Gelfand & Alexandra Schmidt & Sudipto Banerjee & C. Sirmans, 2004. "Nonstationary multivariate process modeling through spatially varying coregionalization," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 263-312, December.
    7. Zhang, Zhengzheng & Parker, Richard M. A. & Charlton, Christopher M. J. & Leckie, George & Browne, William J., 2016. "R2MLwiN: A Package to Run MLwiN from within R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i10).
    8. O’Malley, A. James & Paul, Sudeshna, 2015. "Using retrospective sampling to estimate models of relationship status in large longitudinal social networks," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 35-46.
    9. George Leckie & Robert French & Chris Charlton & William Browne, 2014. "Modeling Heterogeneous Variance–Covariance Components in Two-Level Models," Journal of Educational and Behavioral Statistics, , vol. 39(5), pages 307-332, October.
    10. Browne, William J., 2006. "MCMC algorithms for constrained variance matrices," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1655-1677, April.

    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:biomet:v:63:y:2007:i:1:p:280-289. 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: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.