Key result
Novel mixture model effectively estimates ischaemic stroke mortality in small samples.
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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Ng et al. (2004) studied Ischaemic stroke. Two-component survival mixture model with random effects was evaluated on Ischaemic stroke-specific mortality. An EM-based two-component survival mixture model with random effects adjustment effectively models ischaemic stroke-specific mortality in a small sample setting.
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