IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v40y2002i4p759-774.html
   My bibliography  Save this article

Influence diagnostics for generalized linear mixed models: applications to clustered data

Author

Listed:
  • Xiang, Liming
  • Tse, Siu-Keung
  • Lee, Andy H.

Abstract

No abstract is available for this item.

Suggested Citation

  • Xiang, Liming & Tse, Siu-Keung & Lee, Andy H., 2002. "Influence diagnostics for generalized linear mixed models: applications to clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 759-774, October.
  • Handle: RePEc:eee:csdana:v:40:y:2002:i:4:p:759-774
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(02)00075-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Xiao, Jianguo & Lee, Andy H. & Vemuri, Siva Ram, 1999. "Mixture distribution analysis of length of hospital stay for efficient funding," Socio-Economic Planning Sciences, Elsevier, vol. 33(1), pages 39-59, March.
    2. Lee, Andy H. & Fung, Wing K., 1997. "Confirmation of multiple outliers in generalized linear and nonlinear regressions," Computational Statistics & Data Analysis, Elsevier, vol. 25(1), pages 55-65, July.
    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. Xu, Liang & Lee, Sik-Yum & Poon, Wai-Yin, 2006. "Deletion measures for generalized linear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1131-1146, November.
    2. Xiang, Liming & Yau, Kelvin K.W. & Tse, S.K. & Lee, Andy H., 2007. "Influence diagnostics for random effect survival models: Application to a recurrent infection study for kidney patients on portable dialysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5977-5993, August.
    3. Julio M. Singer & Francisco M.M. Rocha & Juvêncio S. Nobre, 2017. "Graphical Tools for Detecting Departures from Linear Mixed Model Assumptions and Some Remedial Measures," International Statistical Review, International Statistical Institute, vol. 85(2), pages 290-324, August.
    4. 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.
    5. Manor, Orly & Zucker, D.M.David M., 2004. "Small sample inference for the fixed effects in the mixed linear model," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 801-817, July.
    6. Pinho, Luis Gustavo B. & Nobre, Juvêncio S. & Singer, Julio M., 2015. "Cook’s distance for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 126-136.
    7. Li, Zaixing & Xu, Wangli & Zhu, Lixing, 2009. "Influence diagnostics and outlier tests for varying coefficient mixed models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2002-2017, October.

    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. Sara Dias & Valeska Andreozzi & Rosário Martins, 2013. "Analysis of HIV/AIDS DRG in Portugal: a hierarchical finite mixture model," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(5), pages 715-723, October.
    2. Yun Zhao & Andy Lee & Kelvin Yau & Geoffrey McLachlan, 2011. "Assessing the adequacy of Weibull survival models: a simulated envelope approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2089-2097.
    3. Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.
    4. Eva Williford & Valerie Haley & Louise-Anne McNutt & Victoria Lazariu, 2020. "Dealing with highly skewed hospital length of stay distributions: The use of Gamma mixture models to study delivery hospitalizations," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-18, April.
    5. Chungkham Singh & Laishram Ladusingh, 2010. "Inpatient length of stay: a finite mixture modeling analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 119-126, April.
    6. Akouemo, Hermine N. & Povinelli, Richard J., 2016. "Probabilistic anomaly detection in natural gas time series data," International Journal of Forecasting, Elsevier, vol. 32(3), pages 948-956.
    7. Liming Xiang & Andy Lee & Siu-Keung Tse, 2003. "Assessing local cluster influence in generalized linear mixed models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(4), pages 349-359.
    8. Zudi Lu & Yer Van Hui & Andy H. Lee, 2003. "Minimum Hellinger Distance Estimation for Finite Mixtures of Poisson Regression Models and Its Applications," Biometrics, The International Biometric Society, vol. 59(4), pages 1016-1026, December.
    9. Yau, Kelvin K. W. & Lee, Andy H. & Ng, Angus S. K., 2003. "Finite mixture regression model with random effects: application to neonatal hospital length of stay," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 359-366, January.
    10. Yick, John S. & Lee, Andy H., 1998. "Unmasking outliers in two-way contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 69-79, November.

    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:eee:csdana:v:40:y:2002:i:4:p:759-774. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.