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Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks

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  • Paul Blanche
  • Cécile Proust-Lima
  • Lucie Loubère
  • Claudine Berr
  • Jean-François Dartigues
  • Hélène Jacqmin-Gadda

Abstract

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Suggested Citation

  • Paul Blanche & Cécile Proust-Lima & Lucie Loubère & Claudine Berr & Jean-François Dartigues & Hélène Jacqmin-Gadda, 2015. "Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks," Biometrics, The International Biometric Society, vol. 71(1), pages 102-113, March.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:1:p:102-113
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    File URL: http://hdl.handle.net/10.1111/biom.12232
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    References listed on IDEAS

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    1. Dimitris Rizopoulos, 2011. "Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 67(3), pages 819-829, September.
    2. Daniel Commenges & Benoit Liquet & Cécile Proust-Lima, 2012. "Choice of Prognostic Estimators in Joint Models by Estimating Differences of Expected Conditional Kullback–Leibler Risks," Biometrics, The International Biometric Society, vol. 68(2), pages 380-387, June.
    3. 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.
    4. Layla Parast & Su-Chun Cheng & Tianxi Cai, 2012. "Landmark Prediction of Long-Term Survival Incorporating Short-Term Event Time Information," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1492-1501, December.
    5. 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.
    6. Martin W. McIntosh & Margaret Sullivan Pepe, 2002. "Combining Several Screening Tests: Optimality of the Risk Score," Biometrics, The International Biometric Society, vol. 58(3), pages 657-664, September.
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    Citations

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    Cited by:

    1. Liang Li & Sheng Luo & Bo Hu & Tom Greene, 2017. "Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 357-378, December.
    2. Gámiz, María Luz & Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch, 2022. "Missing link survival analysis with applications to available pandemic data," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    3. Graeme L. Hickey & Pete Philipson & Andrea Jorgensen & Ruwanthi Kolamunnage‐Dona, 2018. "A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1105-1123, October.
    4. Marvin N. Wright & Sasmita Kusumastuti & Laust H. Mortensen & Rudi G. J. Westendorp & Thomas A. Gerds, 2021. "Personalised need of care in an ageing society: The making of a prediction tool based on register data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1199-1219, October.
    5. Qing Liu & Gong Tang & Joseph P. Costantino & Chung‐Chou H. Chang, 2020. "Landmark proportional subdistribution hazards models for dynamic prediction of cumulative incidence functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1145-1162, November.
    6. Paul Blanche & Thomas A. Gerds & Claus T. Ekstrøm, 2019. "The Wally plot approach to assess the calibration of clinical prediction models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 150-167, January.

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