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Updated: May 17, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Dynamic prediction by landmarking in competing risks
M A Nicolaie1, J C van Houwelingen, T M de Witte
1Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. M.A.Nicolaie@lumc.nl
Abstract:
We propose an extension of the landmark model for ordinary survival data as a new approach to the problem of dynamic prediction in competing risks with time-dependent covariates. We fix a set of landmark time points tLM within the follow-up interval. For each of these landmark time points tLM , we create a landmark data set by selecting individuals at risk at tLM ; we fix the value of the time-dependent covariate in each landmark data set at tLM . We assume Cox proportional hazard models for the cause-specific hazards and consider smoothing the (possibly) time-dependent effect of the covariate for the different landmark data sets. Fitting this model is possible within the standard statistical software. We illustrate the features of the landmark modelling on a real data set on bone marrow transplantation.
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