A random effects model for multistate survival analysis with application to bone marrow transplants
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Updated: Aug 18, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Mouchumi Bhattacharyya1, John P Klein
1Department of Mathematics, University of the Pacific, 3601 Pacific Avenue, Stockton, CA 95211, USA. mbhattacharyya@uop.edu
Abstract:
We present an extension of the non-homogeneous Markov model for a bone marrow transplant recovery process which allows for possible associations between the transition intensities. The associations between intensities are modeled by a correlated gamma frailty model. Based on a parametric model for the conditional transition intensities, we obtain estimates of the model parameters. We use these estimates to make predictions of patient's eventual prognosis given the current medical history of the patient. Estimates of the uncertainty in our predictions are obtained by a modified bootstrap technique.
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