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Spatially Dependent Polya Tree Modeling for Survival Data

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  • Luping Zhao
  • Timothy E. Hanson

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  • Luping Zhao & Timothy E. Hanson, 2011. "Spatially Dependent Polya Tree Modeling for Survival Data," Biometrics, The International Biometric Society, vol. 67(2), pages 391-403, June.
  • Handle: RePEc:bla:biomet:v:67:y:2011:i:2:p:391-403
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01468.x
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    References listed on IDEAS

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    1. Griffin, J.E. & Steel, M.F.J., 2006. "Order-Based Dependent Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 179-194, March.
    2. Hanson, Timothy E., 2006. "Inference for Mixtures of Finite Polya Tree Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1548-1565, December.
    3. David B. Dunson & Natesh Pillai & Ju‐Hyun Park, 2007. "Bayesian density regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 163-183, April.
    4. Brezger, Andreas & Kneib, Thomas & Lang, Stefan, 2005. "BayesX: Analyzing Bayesian Structural Additive Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i11).
    5. Luping Zhao & Timothy E. Hanson & Bradley P. Carlin, 2009. "Mixtures of Polya trees for flexible spatial frailty survival modelling," Biometrika, Biometrika Trust, vol. 96(2), pages 263-276.
    6. Zeng, Donglin & Lin, D.Y. & Yin, Guosheng, 2005. "Maximum Likelihood Estimation for the Proportional Odds Model With Random Effects," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 470-483, June.
    7. 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.
    8. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    9. Hennerfeind, Andrea & Brezger, Andreas & Fahrmeir, Ludwig, 2006. "Geoadditive Survival Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1065-1075, September.
    10. Henderson R. & Shimakura S. & Gorst D., 2002. "Modeling Spatial Variation in Leukemia Survival Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 965-972, December.
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    Cited by:

    1. Kehui Yao & Jun Zhu & Daniel J. O'Brien & Daniel Walsh, 2023. "Bayesian spatio‐temporal survival analysis for all types of censoring with application to a wildlife disease study," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
    2. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    3. Haiming Zhou & Timothy Hanson & Jiajia Zhang, 2017. "Generalized accelerated failure time spatial frailty model for arbitrarily censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 495-515, July.
    4. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    5. Y. Hagar & M. Hayden & C. Wiedinmyer & V. Dukic, 2017. "Comparison of Models Analyzing a Small Number of Observed Meningitis Cases in Navrongo, Ghana," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(1), pages 76-104, March.

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