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Meta-analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling

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  • Debashis Ghosh
  • Jeremy M. G. Taylor
  • Daniel J. Sargent

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  • Debashis Ghosh & Jeremy M. G. Taylor & Daniel J. Sargent, 2012. "Meta-analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling," Biometrics, The International Biometric Society, vol. 68(1), pages 226-232, March.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:1:p:226-232
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01633.x
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    References listed on IDEAS

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    1. Debashis Ghosh, 2008. "Semiparametric Inference for Surrogate Endpoints with Bivariate Censored Data," Biometrics, The International Biometric Society, vol. 64(1), pages 149-156, March.
    2. Debashis Ghosh, 2009. "On Assessing Surrogacy in a Single Trial Setting Using a Semicompeting Risks Paradigm," Biometrics, The International Biometric Society, vol. 65(2), pages 521-529, June.
    3. Michael E. Tipping & Christopher M. Bishop, 1999. "Probabilistic Principal Component Analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 611-622.
    4. Tomasz Burzykowski & Geert Molenberghs & Marc Buyse & Helena Geys & Didier Renard, 2001. "Validation of surrogate end points in multiple randomized clinical trials with failure time end points," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(4), pages 405-422.
    5. Yue Wang & Jeremy M. G. Taylor, 2002. "A Measure of the Proportion of Treatment Effect Explained by a Surrogate Marker," Biometrics, The International Biometric Society, vol. 58(4), pages 803-812, December.
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    Cited by:

    1. Kyu Ha Lee & Virginie Rondeau & Sebastien Haneuse, 2017. "Accelerated failure time models for semi‐competing risks data in the presence of complex censoring," Biometrics, The International Biometric Society, vol. 73(4), pages 1401-1412, December.
    2. Fan, Caiyun & Lu, Wenbin & Zhou, Yong, 2021. "Testing error heterogeneity in censored linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).

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