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Time-Dependent Predictive Accuracy in the Presence of Competing Risks

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  • P. Saha
  • P. J. Heagerty

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  • P. Saha & P. J. Heagerty, 2010. "Time-Dependent Predictive Accuracy in the Presence of Competing Risks," Biometrics, The International Biometric Society, vol. 66(4), pages 999-1011, December.
  • Handle: RePEc:bla:biomet:v:66:y:2010:i:4:p:999-1011
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01375.x
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    References listed on IDEAS

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    1. Yingye Zheng & Patrick J. Heagerty, 2007. "Prospective Accuracy for Longitudinal Markers," Biometrics, The International Biometric Society, vol. 63(2), pages 332-341, June.
    2. Patrick J. Heagerty & Yingye Zheng, 2005. "Survival Model Predictive Accuracy and ROC Curves," Biometrics, The International Biometric Society, vol. 61(1), pages 92-105, March.
    3. J. B. Copas, 2002. "Overestimation of the receiver operating characteristic curve for logistic regression," Biometrika, Biometrika Trust, vol. 89(2), pages 315-331, June.
    4. Thomas H. Scheike & Torben Martinussen, 2004. "On Estimation and Tests of Time‐Varying Effects in the Proportional Hazards Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 51-62, March.
    5. R. Schoop & E. Graf & M. Schumacher, 2008. "Quantifying the Predictive Performance of Prognostic Models for Censored Survival Data with Time-Dependent Covariates," Biometrics, The International Biometric Society, vol. 64(2), pages 603-610, June.
    6. Zongwu Cai & Yanqing Sun, 2003. "Local Linear Estimation for Time‐Dependent Coefficients in Cox's Regression Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 93-111, March.
    7. Michael Schemper & Robin Henderson, 2000. "Predictive Accuracy and Explained Variation in Cox Regression," Biometrics, The International Biometric Society, vol. 56(1), pages 249-255, March.
    8. Ronghui Xu & John O'Quigley, 2000. "Proportional hazards estimate of the conditional survival function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 667-680.
    9. Patrick J. Heagerty & Thomas Lumley & Margaret S. Pepe, 2000. "Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker," Biometrics, The International Biometric Society, vol. 56(2), pages 337-344, June.
    10. Dikta, Gerhard, 1990. "Bootstrap approximation of nearest neighbor regression function estimates," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 213-229, February.
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    Cited by:

    1. Yingye Zheng & Tianxi Cai & Yuying Jin & Ziding Feng, 2012. "Evaluating Prognostic Accuracy of Biomarkers under Competing Risk," Biometrics, The International Biometric Society, vol. 68(2), pages 388-396, June.
    2. Debashis Ghosh, 2016. "A Modified Risk Set Approach to Biomarker Evaluation Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 395-406, October.
    3. Song Zhang & Yang Qu & Yu Cheng & Oscar L. Lopez & Abdus S. Wahed, 2022. "Prognostic accuracy for predicting ordinal competing risk outcomes using ROC surfaces," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(1), pages 1-22, January.
    4. Weining Shen & Jing Ning & Ying Yuan, 2015. "A direct method to evaluate the time-dependent predictive accuracy for biomarkers," Biometrics, The International Biometric Society, vol. 71(2), pages 439-449, June.
    5. Pablo Mart�nez-Camblor & Jacobo de U�a-�lvarez & Carmen D�az Corte, 2015. "Expanded renal transplantation: a competing risk model approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2539-2553, December.
    6. Jing Zhang & Jing Ning & Ruosha Li, 2023. "Evaluating Dynamic Discrimination Performance of Risk Prediction Models for Survival Outcomes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(2), pages 353-371, July.

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