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A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data With Application to the Breast Cancer Prevention Trial

Author

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  • Wang, C.
  • Daniels, M. J.
  • Scharfstein, D. O.
  • Land, S.
Abstract
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Suggested Citation

  • Wang, C. & Daniels, M. J. & Scharfstein, D. O. & Land, S., 2010. "A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data With Application to the Breast Cancer Prevention Trial," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1333-1346.
    • Handle: RePEc:bes:jnlasa:v:105:i:492:y:2010:p:1333-1346
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    File URL: http://pubs.amstat.org/doi/abs/10.1198/jasa.2010.ap09321
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    Cited by:

    1. A. R. Linero, 2017. "Bayesian nonparametric analysis of longitudinal studies in the presence of informative missingness," Biometrika, Biometrika Trust, vol. 104(2), pages 327-341.
    2. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    3. Antonio R. Linero & Michael J. Daniels, 2015. "A Flexible Bayesian Approach to Monotone Missing Data in Longitudinal Studies With Nonignorable Missingness With Application to an Acute Schizophrenia Clinical Trial," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 45-55, March.

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