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A Bayesian Approach for Joint Modeling of Cluster Size and Subunit-Specific Outcomes

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  • David B. Dunson
  • Zhen Chen
  • Jean Harry

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  • 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.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:3:p:521-530
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    File URL: http://hdl.handle.net/10.1111/1541-0420.00062
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    References listed on IDEAS

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    1. James H. Albert & Siddhartha Chib, 2001. "Sequential Ordinal Modeling with Applications to Survival Data," Biometrics, The International Biometric Society, vol. 57(3), pages 829-836, September.
    2. N. Longford & B. Muthén, 1992. "Factor analysis for clustered observations," Psychometrika, Springer;The Psychometric Society, vol. 57(4), pages 581-597, December.
    3. Asim Ansari & Kamel Jedidi, 2000. "Bayesian factor analysis for multilevel binary observations," Psychometrika, Springer;The Psychometric Society, vol. 65(4), pages 475-496, December.
    4. Meredith M. Regan & Paul J. Catalano, 1999. "Likelihood Models for Clustered Binary and Continuous Out comes: Application to Developmental Toxicology," Biometrics, The International Biometric Society, vol. 55(3), pages 760-768, September.
    5. David B. Dunson & Sally D. Perreault, 2001. "Factor Analytic Models of Clustered Multivariate Data with Informative Censoring," Biometrics, The International Biometric Society, vol. 57(1), pages 302-308, March.
    6. D. B. Dunson, 2000. "Bayesian latent variable models for clustered mixed outcomes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 355-366.
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    Cited by:

    1. Matthew W. Wheeler & A. John Bailer, 2009. "Benchmark Dose Estimation Incorporating Multiple Data Sources," Risk Analysis, John Wiley & Sons, vol. 29(2), pages 249-256, February.
    2. Ling Chen & Yanqin Feng & Jianguo Sun, 2017. "Regression analysis of clustered failure time data with informative cluster size under the additive transformation models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 651-670, October.
    3. Claudia Czado & Anette Heyn & Gernot Müller, 2011. "Modeling individual migraine severity with autoregressive ordered probit models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(1), pages 101-121, March.
    4. Julie S. Najita & Yi Li & Paul J. Catalano, 2009. "A novel application of a bivariate regression model for binary and continuous outcomes to studies of fetal toxicity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 555-573, September.
    5. Reem Aljarallah & Samer A Kharroubi, 2021. "Use of Bayesian Markov Chain Monte Carlo Methods to Model Kuwait Medical Genetic Center Data: An Application to Down Syndrome and Mental Retardation," Mathematics, MDPI, vol. 9(3), pages 1-11, January.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Shuling Liu & Amita K. Manatunga & Limin Peng & Michele Marcus, 2017. "A joint modeling approach for multivariate survival data with random length," Biometrics, The International Biometric Society, vol. 73(2), pages 666-677, June.
    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. Ralitza V. Gueorguieva, 2005. "Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit-Specific Outcomes," Biometrics, The International Biometric Society, vol. 61(3), pages 862-866, September.
    13. 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.
    14. Sean M. O'Brien & David B. Dunson, 2004. "Bayesian Multivariate Logistic Regression," Biometrics, The International Biometric Society, vol. 60(3), pages 739-746, September.
    15. 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.
    16. Julie S. Najita & Paul J. Catalano, 2013. "On Determining the BMD from Multiple Outcomes in Developmental Toxicity Studies when One Outcome is Intentionally Missing," Risk Analysis, John Wiley & Sons, vol. 33(8), pages 1500-1509, August.
    17. 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.
    18. Lanjia Lin & Dipankar Bandyopadhyay & Stuart R. Lipsitz & Debajyoti Sinha, 2010. "Association Models for Clustered Data with Binary and Continuous Responses," Biometrics, The International Biometric Society, vol. 66(1), pages 287-293, March.
    19. Michael R. Elliott & Marshall M. Joffe & Zhen Chen, 2006. "A Potential Outcomes Approach to Developmental Toxicity Analyses," Biometrics, The International Biometric Society, vol. 62(2), pages 352-360, June.
    20. Kassandra Fronczyk & Athanasios Kottas, 2017. "Risk Assessment for Toxicity Experiments with Discrete and Continuous Outcomes: A Bayesian Nonparametric Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 585-601, December.

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