Modelling the distribution of ischaemic stroke‐specific survival time using an EM‐based mixture approach with random effects adjustment
Shu‐Kay Ng, Geoffrey John McLachlan, Kelvin K.W. Yau, Andy H. Lee · Statistics in Medicine · 2004
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.