A Tutorial on Markov Renewal and Semi-Markov Proportional Hazards Model

Bibliographic Details
Title: A Tutorial on Markov Renewal and Semi-Markov Proportional Hazards Model
Authors: Cuicizion, Eliuvish, Ri, Itsugo, Holmes, Elaine, Chern, Jawad
Publication Year: 2025
Collection: Statistics
Subject Terms: Statistics - Applications, Statistics - Computation
More Details: Transition probability estimation plays a critical role in multi-state modeling, especially in clinical research. This paper investigates the application of semi-Markov and Markov renewal frameworks to the EBMT dataset, focusing on six clinical states encountered during hematopoietic stem cell transplantation. By comparing Aalen-Johansen (AJ) and Dabrowska-Sun-Horowitz (DSH) estimators, we demonstrate that semi-Markov models, which incorporate sojourn times, provide a more nuanced and temporally sensitive depiction of patient trajectories compared to memoryless Markov models. The DSH estimator consistently yields smoother probability curves, particularly for transitions involving prolonged states. We use empirical process theory and Burkholder-Davis-Gundy inequality to show weak convergence of the estimator. Future work includes extending the framework to accommodate advanced covariate structures and non-Markovian dynamics.
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2502.03479
Accession Number: edsarx.2502.03479
Database: arXiv
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