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Estimating survival functions after stcox with time-varying coefficients

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  • Constantin Ruhe

    (University of Konstanz)

Abstract

In many applications of the Cox model, the proportional-hazards assumption is implausible. In these cases, the solution to nonproportional hazards usually consists of modeling the effect of the variable of interest and its interaction effect with some function of time. Although Stata provides a command to implement this interaction in stcox, it does not allow the typical visualizations using stcurve if stcox was estimated with the tvc() option. In this article, I provide a short workaround that estimates the survival function after stcox with timedependent coefficients. I introduce and describe the scurve tvc command, which automates this procedure and allows users to easily visualize survival functions for models with time-varying effects. Copyright 2016 by StataCorp LP.

Suggested Citation

  • Constantin Ruhe, 2016. "Estimating survival functions after stcox with time-varying coefficients," Stata Journal, StataCorp LP, vol. 16(4), pages 867-879, December.
    • Handle: RePEc:tsj:stataj:v:16:y:2016:i:4:p:867-879
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    Cited by:

    1. Simon, James David & D'Andrade, Amy & Hsu, Hsun-Ta, 2021. "The intersection of child welfare services and public assistance: An analysis of dual-system involvement and successful family preservation completion on a maltreatment re-report," Children and Youth Services Review, Elsevier, vol. 127(C).
    2. Steffen Hurka & Maximilian Haag, 2020. "Policy complexity and legislative duration in the European Union," European Union Politics, , vol. 21(1), pages 87-108, March.

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