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Understanding Landmarking and Its Relation with Time-Dependent Cox Regression

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  • Hein Putter

    (Leiden University Medical Center)

  • Hans C. Houwelingen

    (Leiden University Medical Center)

Abstract

Time-dependent Cox regression and landmarking are the two most commonly used approaches for the analysis of time-dependent covariates in time-to-event data. The estimated effect of the time-dependent covariate in a landmarking analysis is based on the value of the time-dependent covariate at the landmark time point, after which the time-dependent covariate may change value. In this note we derive expressions for the (time-varying) regression coefficient of the time-dependent covariate in the landmark analysis, in terms of the regression coefficient and baseline hazard of the time-dependent Cox regression. These relations are illustrated using simulation studies and using the Stanford heart transplant data.

Suggested Citation

  • Hein Putter & Hans C. Houwelingen, 2017. "Understanding Landmarking and Its Relation with Time-Dependent Cox Regression," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 489-503, December.
    • Handle: RePEc:spr:stabio:v:9:y:2017:i:2:d:10.1007_s12561-016-9157-9
    DOI: 10.1007/s12561-016-9157-9
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    References listed on IDEAS

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    1. Hans C. Van Houwelingen, 2007. "Dynamic Prediction by Landmarking in Event History Analysis," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(1), pages 70-85, March.
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