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International Conference on Computational Science and Its Applications

ICCSA 2017: Computational Science and Its Applications – ICCSA 2017 pp 621–631Cite as

Assessing the Predictive Performance of Survival Models with Longitudinal Data

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10405))

Abstract

In many follow-up studies, different types of outcomes are collected including longitudinal measurements and time-to-event outcomes. Commonly, it is of interest to study the association between them. Different regression modelling techniques have been proposed in the literature to study such association. In this paper, we will focus on two of them: two-stage models and joint modelling framework and compare them in terms of the predictive capacity of the time-to-event model. Our interest is twofold: discussing the occurrence of bias estimations and predictive capacity of the models in short-term and long-term mortality in our particular case study, Cardiac Resynchronization Therapy (CRT).

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Author information

Authors and Affiliations

  1. Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela, 15782, Santiago de Compostela, A Coruña, Spain

    Ipek Guler & Carmen Cadarso-Suárez

  2. Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Universiteit Hasselt, Hasselt, Belgium

    Christel Faes

  3. Clinical Epidemiology Unit, Hospital Clinico Santiago de Compostela, A Coruña, Spain

    Francisco Gude

Authors
  1. Ipek Guler
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  2. Christel Faes
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  3. Francisco Gude
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  4. Carmen Cadarso-Suárez
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Corresponding author

Correspondence to Ipek Guler .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Trieste, Trieste, Italy

    Giuseppe Borruso

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  9. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  10. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

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© 2017 Springer International Publishing AG

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Cite this paper

Guler, I., Faes, C., Gude, F., Cadarso-Suárez, C. (2017). Assessing the Predictive Performance of Survival Models with Longitudinal Data. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10405. Springer, Cham. https://doi.org/10.1007/978-3-319-62395-5_43

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  • DOI: https://doi.org/10.1007/978-3-319-62395-5_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62394-8

  • Online ISBN: 978-3-319-62395-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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