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Updated: Jun 21, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Pseudo-observations in survival analysis
Per Kragh Andersen1, Maja Pohar Perme
1Department of Biostatistics, University of Copenhagen, Copenhagen K, Denmark. P.K.Andersen@biostat.ku.dk
Abstract:
We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competing risks cumulative incidence function. Graphical and numerical methods for assessing goodness-of-fit for hazard regression models and for the Fine-Gray model in competing risks studies based on pseudo-observations are also reviewed. Sensitivity to covariate-dependent censoring is studied. The methods are illustrated using a data set from bone marrow transplantation.
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