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A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data

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  • Kiranmoy Das
  • Michael J. Daniels

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  • Kiranmoy Das & Michael J. Daniels, 2014. "A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data," Biometrics, The International Biometric Society, vol. 70(1), pages 33-43, March.
    • Handle: RePEc:bla:biomet:v:70:y:2014:i:1:p:33-43
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    File URL: http://hdl.handle.net/10.1111/biom.12133
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    References listed on IDEAS

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    1. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, January.
    2. Dunson, David B. & Xue, Ya & Carin, Lawrence, 2008. "The Matrix Stick-Breaking Process: Flexible Bayes Meta-Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 317-327, March.
    3. Wei Biao Wu, 2003. "Nonparametric estimation of large covariance matrices of longitudinal data," Biometrika, Biometrika Trust, vol. 90(4), pages 831-844, December.
    4. Jianxin Pan, 2003. "On modelling mean-covariance structures in longitudinal studies," Biometrika, Biometrika Trust, vol. 90(1), pages 239-244, March.
    5. Jabu S. Sithole & Peter W. Jones, 2007. "Bivariate Longitudinal Model for Detecting Prescribing Change in Two Drugs Simultaneously with Correlated Errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(3), pages 339-352.
    6. Michael J. Daniels, 2002. "Bayesian analysis of covariance matrices and dynamic models for longitudinal data," Biometrika, Biometrika Trust, vol. 89(3), pages 553-566, August.
    7. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, January.
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    Cited by:

    1. Jiguo Cao & Liangliang Wang & Zhongwen Huang & Junyi Gai & Rongling Wu, 2017. "Functional Mapping of Multiple Dynamic Traits," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(1), pages 60-75, March.
    2. Hemant Kulkarni & Jayabrata Biswas & Kiranmoy Das, 2019. "A joint quantile regression model for multiple longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 453-473, December.
    3. Jayabrata Biswas & Kiranmoy Das, 2021. "A Bayesian quantile regression approach to multivariate semi-continuous longitudinal data," Computational Statistics, Springer, vol. 36(1), pages 241-260, March.
    4. Kiranmoy Das & Bhuvanesh Pareek & Sarah Brown & Pulak Ghosh, 2022. "A semi-parametric Bayesian dynamic hurdle model with an application to the health and retirement study," Computational Statistics, Springer, vol. 37(2), pages 837-863, April.
    5. Lihui Zhao & Tom Chen & Vladimir Novitsky & Rui Wang, 2021. "Joint penalized spline modeling of multivariate longitudinal data, with application to HIV‐1 RNA load levels and CD4 cell counts," Biometrics, The International Biometric Society, vol. 77(3), pages 1061-1074, September.
    6. Kiranmoy Das, 2016. "A semiparametric Bayesian approach for joint modeling of longitudinal trait and event time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2850-2865, November.
    7. Kiranmoy Das & Bhuvanesh Pareek & Sarah Brown & Pulak Ghosh, 2017. "A Semiparametric Bayesian Approach to a New Dynamic Zero-Inflated Model," Working Papers 2017001, The University of Sheffield, Department of Economics.

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