IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v73y2017i1p260-270.html
   My bibliography  Save this article

Tumor dormancy and frailty models: A novel approach

Author

Listed:
  • Paola M. V. Rancoita
  • Morten Valberg
  • Romano Demicheli
  • Elia Biganzoli
  • Clelia Di Serio

Abstract

No abstract is available for this item.

Suggested Citation

  • Paola M. V. Rancoita & Morten Valberg & Romano Demicheli & Elia Biganzoli & Clelia Di Serio, 2017. "Tumor dormancy and frailty models: A novel approach," Biometrics, The International Biometric Society, vol. 73(1), pages 260-270, March.
  • Handle: RePEc:bla:biomet:v:73:y:2017:i:1:p:260-270
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12559
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. J. Goeman & S. Le Cessie & R. J. Baatenburg de Jong & S. A. Van De Geer, 2004. "Predicting survival using disease history: a model combining relative survival and frailty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(1), pages 21-34, February.
    2. J. Heckman & B. Singer, 1984. "The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 231-241.
    3. Boracchi, Patrizia & Biganzoli, Elia & Marubini, Ettore, 2003. "Joint modelling of cause-specific hazard functions with cubic splines: an application to a large series of breast cancer patients," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 243-262, February.
    4. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 403-409.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    2. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    3. Eil, David & Lien, Jaimie W., 2014. "Staying ahead and getting even: Risk attitudes of experienced poker players," Games and Economic Behavior, Elsevier, vol. 87(C), pages 50-69.
    4. Bijwaard, Govert, 2011. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," IZA Discussion Papers 5748, Institute of Labor Economics (IZA).
    5. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
    6. James J. Heckman & Christopher R. Taber, 1994. "Econometric Mixture Models and More General Models for Unobservables in Duration Analysis," NBER Technical Working Papers 0157, National Bureau of Economic Research, Inc.
    7. David MARGOLIS, 2008. "Unemployment Insurance Versus Individual Unemployment Accounts and Transitions to Formal Versus Informal Sector Jobs," Working Papers 2008-35, Center for Research in Economics and Statistics.
    8. Christian N. Brinch, 2011. "Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 343-350, July.
    9. Govert Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.
    10. Bijwaard, Govert, 2021. "Educational Differences in Mortality and Hospitalisation for Cardiovascular Diseases for Males," IZA Discussion Papers 14507, Institute of Labor Economics (IZA).
    11. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    12. Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(2), pages 349-354, April.
    13. Taha Rashidi & Abolfazl Mohammadian & Frank Koppelman, 2011. "Modeling interdependencies between vehicle transaction, residential relocation and job change," Transportation, Springer, vol. 38(6), pages 909-932, November.
    14. Guido Imbens & Lisa Lynch, 2006. "Re-employment probabilities over the business cycle," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 5(2), pages 111-134, August.
    15. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460, Elsevier.
    16. Barros, Ricardo Paes de, 2010. "The Impact of Social Interventions: Nonparametric Identification from Choice-Based Samples," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(2), December.
    17. Jaap H. Abbring, 2012. "Mixed Hitting‐Time Models," Econometrica, Econometric Society, vol. 80(2), pages 783-819, March.
    18. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.
    19. Jaap H. Abbring, 2010. "Identification of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 367-394, September.
    20. Frijters, Paul, 2002. "The non-parametric identification of lagged duration dependence," Economics Letters, Elsevier, vol. 75(3), pages 289-292, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:73:y:2017:i:1:p:260-270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.