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Updated: Oct 7, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Inference in randomized studies with informative censoring and discrete time-to-event endpoints
D Scharfstein1, J M Robins, W Eddings
1Department of Biostatistics, Johns Hopkins School of Hygiene and Public Health, Baltimore, Maryland 21025, USA. dscharf@jhsph.edu
Abstract:
In this article, we present a method for estimating and comparing the treatment-specific distributions of a discrete time-to-event variable from right-censored data. Our method allows for (1) adjustment for informative censoring due to measured prognostic factors for time to event and censoring and (2) quantification of the sensitivity of the inference to residual dependence between time to event and censoring due to unmeasured factors. We develop our approach in the context of a randomized trial for the treatment of chronic schizophrenia. We perform a simulation study to assess the practical performance of our methodology.
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