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A hierarchical modeling approach for risk assessment in developmental toxicity studies

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  • Faes, Christel
  • Geys, Helena
  • Aerts, Marc
  • Molenberghs, Geert

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  • 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.
  • Handle: RePEc:eee:csdana:v:51:y:2006:i:3:p:1848-1861
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    References listed on IDEAS

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    1. Paul Catalano & Louise Ryan & Daniel Scharfstein, 1994. "Modeling Fetal Death and Malformation in Developmental Toxicity Studies," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 629-637, August.
    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. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    4. 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.
    5. Ronald J. Bosch & David Wypij & Louise M. Ryan, 1996. "A Semiparametric Approach to Risk Assessment for Quantitative Outcomes," Risk Analysis, John Wiley & Sons, vol. 16(5), pages 657-665, October.
    6. Andrew S. Allen & Huiman X. Barnhart, 2002. "Joint Models for Toxicology Studies with Dose‐Dependent Number of Implantations," Risk Analysis, John Wiley & Sons, vol. 22(6), pages 1165-1173, December.
    7. 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.
    8. Patrick Royston & Douglas G. Altman, 1994. "Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(3), pages 429-453, September.
    9. Molenberghs, Geert & Declerck, Lieven & Aerts, Marc, 1998. "Misspecifying the likelihood for clustered binary data," Computational Statistics & Data Analysis, Elsevier, vol. 26(3), pages 327-349, January.
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    Cited by:

    1. Jin‐Zhu Yu & Hiba Baroud, 2019. "Quantifying Community Resilience Using Hierarchical Bayesian Kernel Methods: A Case Study on Recovery from Power Outages," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1930-1948, September.
    2. 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.
    3. 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.
    4. Pryseley, Assam & Tchonlafi, Clotaire & Verbeke, Geert & Molenberghs, Geert, 2011. "Estimating negative variance components from Gaussian and non-Gaussian data: A mixed models approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1071-1085, February.
    5. Ander Wilson & David M. Reif & Brian J. Reich, 2014. "Hierarchical dose–response modeling for high-throughput toxicity screening of environmental chemicals," Biometrics, The International Biometric Society, vol. 70(1), pages 237-246, March.

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