IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i1p218-227.html
   My bibliography  Save this article

Test of Marginal Compatibility and Smoothing Methods for Exchangeable Binary Data with Unequal Cluster Sizes

Author

Listed:
  • Zhen Pang
  • Anthony Y. C. Kuk

Abstract

No abstract is available for this item.

Suggested Citation

  • Zhen Pang & Anthony Y. C. Kuk, 2007. "Test of Marginal Compatibility and Smoothing Methods for Exchangeable Binary Data with Unequal Cluster Sizes," Biometrics, The International Biometric Society, vol. 63(1), pages 218-227, March.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:1:p:218-227
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00678.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. Anthony Y. C. Kuk, 2004. "A litter‐based approach to risk assessment in developmental toxicity studies via a power family of completely monotone functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 369-386, April.
    2. Anthony Y. C. Kuk, 2003. "A generalized estimating equation approach to modelling foetal response in developmental toxicity studies when the number of implants is dose dependent," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 51-61, January.
    3. Martin S. Ridout & Clarice G. B. Demétrio & David Firth, 1999. "Estimating Intraclass Correlation for Binary Data," Biometrics, The International Biometric Society, vol. 55(1), pages 137-148, March.
    4. Catalina Stefanescu & Bruce W. Turnbull, 2003. "Likelihood Inference for Exchangeable Binary Data with Varying Cluster Sizes," Biometrics, The International Biometric Society, vol. 59(1), pages 18-24, March.
    5. Patricia M. E. Altham, 1978. "Two Generalizations of the Binomial Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 27(2), pages 162-167, June.
    6. John M. Williamson & Somnath Datta & Glen A. Satten, 2003. "Marginal Analyses of Clustered Data When Cluster Size Is Informative," Biometrics, The International Biometric Society, vol. 59(1), pages 36-42, March.
    7. David B. Dunson & Zhen Chen & Jean Harry, 2003. "A Bayesian Approach for Joint Modeling of Cluster Size and Subunit-Specific Outcomes," Biometrics, The International Biometric Society, vol. 59(3), pages 521-530, September.
    8. Zhen Pang & Anthony Y. C. Kuk, 2005. "A Shared Response Model for Clustered Binary Data in Developmental Toxicity Studies," Biometrics, The International Biometric Society, vol. 61(4), pages 1076-1084, December.
    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. Kolossiatis, M. & Griffin, J.E. & Steel, M.F.J., 2011. "Modeling overdispersion with the normalized tempered stable distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2288-2301, July.
    2. Yu, Chang & Zelterman, Daniel, 2008. "Sums of exchangeable Bernoulli random variables for family and litter frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1636-1649, January.
    3. Faes, Christel & Geys, Helena & Aerts, Marc & Molenberghs, Geert, 2006. "A hierarchical modeling approach for risk assessment in developmental toxicity studies," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1848-1861, December.
    4. Zhen Pang & Anthony Y. C. Kuk, 2005. "A Shared Response Model for Clustered Binary Data in Developmental Toxicity Studies," Biometrics, The International Biometric Society, vol. 61(4), pages 1076-1084, December.
    5. Jaakko Nevalainen & Somnath Datta & Hannu Oja, 2014. "Inference on the marginal distribution of clustered data with informative cluster size," Statistical Papers, Springer, vol. 55(1), pages 71-92, February.
    6. Tounkara Fodé & Rivest Louis-Paul, 2014. "Some New Random Effect Models for Correlated Binary Responses," Dependence Modeling, De Gruyter, vol. 2(1), pages 1-15, December.
    7. Guangyong Zou & Allan Donner, 2004. "Confidence Interval Estimation of the Intraclass Correlation Coefficient for Binary Outcome Data," Biometrics, The International Biometric Society, vol. 60(3), pages 807-811, September.
    8. Hui-Xiu Zhao & Jin-Guan Lin, 2013. "An approximately optimal non-parametric procedure for analyzing exchangeable binary data with random cluster sizes," Computational Statistics, Springer, vol. 28(5), pages 2029-2047, October.
    9. Chun Yin Lee & Kin Yau Wong & Kwok Fai Lam & Dipankar Bandyopadhyay, 2023. "A semiparametric joint model for cluster size and subunit‐specific interval‐censored outcomes," Biometrics, The International Biometric Society, vol. 79(3), pages 2010-2022, September.
    10. Glen McGee & Marianthi‐Anna Kioumourtzoglou & Marc G. Weisskopf & Sebastien Haneuse & Brent A. Coull, 2020. "On the interplay between exposure misclassification and informative cluster size," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1209-1226, November.
    11. Xiaoyun Li & Dipankar Bandyopadhyay & Stuart Lipsitz & Debajyoti Sinha, 2011. "Likelihood Methods for Binary Responses of Present Components in a Cluster," Biometrics, The International Biometric Society, vol. 67(2), pages 629-635, June.
    12. Shaun R. Seaman & Menelaos Pavlou & Andrew J. Copas, 2014. "Methods for observed-cluster inference when cluster size is informative: A review and clarifications," Biometrics, The International Biometric Society, vol. 70(2), pages 449-456, June.
    13. Dette, Holger & Biedermann, Stefanie & Zhu, Wei, 2005. "Geometric construction of optimal designs for dose-responsemodels with two parameters," Technical Reports 2005,08, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    14. Zhang, Xinyan & Sun, Jianguo, 2010. "Regression analysis of clustered interval-censored failure time data with informative cluster size," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1817-1823, July.
    15. Zaigraev, Alexander & Kaniovski, Serguei, 2010. "Exact bounds on the probability of at least k successes in n exchangeable Bernoulli trials as a function of correlation coefficients," Statistics & Probability Letters, Elsevier, vol. 80(13-14), pages 1079-1084, July.
    16. Maria A. Spassova, 2019. "Statistical Approach to Identify Threshold and Point of Departure in Dose–Response Data," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 940-956, April.
    17. McMahon, James M. & Pouget, Enrique R. & Tortu, Stephanie, 2006. "A guide for multilevel modeling of dyadic data with binary outcomes using SAS PROC NLMIXED," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3663-3680, August.
    18. Joanna H. Shih & Michael P. Fay, 2017. "Pearson's chi-square test and rank correlation inferences for clustered data," Biometrics, The International Biometric Society, vol. 73(3), pages 822-834, September.
    19. Yue, Chen & Chen, Shaojie & Sair, Haris I. & Airan, Raag & Caffo, Brian S., 2015. "Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 126-133.
    20. Ling Lan & Dipankar Bandyopadhyay & Somnath Datta, 2017. "Non-parametric regression in clustered multistate current status data with informative cluster size," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 71(1), pages 31-57, January.

    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:218-227. 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.