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Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt

Author

Listed:
  • Hannah Bower

    (Department of Medicine Solna, Karolinska Institutet)

  • Therese M.-L. Andersson

    (Karolinska Institutet)

  • Michael J. Crowther

    (Karolinska Institutet)

  • Paul C. Lambert

    (Department of Health Sciences, University of Leicester)

Abstract

In this article, we describe methodology that allows for multiple timescales using flexible parametric survival models without the need for time splitting. When one fits flexible parametric survival models on the log-hazard scale, numerical integration is required in the log likelihood to fit the model. The use of numerical integration allows incorporation of arbitrary functions of time into the model and hence lends itself to the inclusion of multiple timescales in an appealing way. We describe and exemplify these methods and show how to use the command stmt, which implements these methods, alongside its postestimation commands.

Suggested Citation

  • Hannah Bower & Therese M.-L. Andersson & Michael J. Crowther & Paul C. Lambert, 2022. "Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt," Stata Journal, StataCorp LP, vol. 22(3), pages 679-701, September.
    • Handle: RePEc:tsj:stataj:y:22:y:2022:i:3:p:679-701
    DOI: 10.1177/1536867X221124552
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