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Updated: Aug 23, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Modelling the distribution of ischaemic stroke-specific survival time using an EM-based mixture approach with random
S K Ng1, G J McLachlan, Kelvin K W Yau
1Department of Mathematics, University of Queensland, Brisbane, QLD 4072, Australia. skn@maths.uq.edu.au
Abstract:
A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting.
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